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Huang J, Xu Y, Wen X, Zhu X, Herrera-Viedma E. Deriving priorities from the fuzzy best-worst method matrix and its applications: A perspective of incomplete reciprocal preference relation. Inf Sci (N Y) 2023. [DOI: 10.1016/j.ins.2023.03.125] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/03/2023]
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2
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Deng J, Zhan J, Xu Z, Herrera-Viedma E. Regret-Theoretic Multiattribute Decision-Making Model Using Three-Way Framework in Multiscale Information Systems. IEEE Trans Cybern 2023; 53:3988-4001. [PMID: 35604987 DOI: 10.1109/tcyb.2022.3173374] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/18/2023]
Abstract
The existing multiattribute decision-making (MADM) methods on multiscale information systems (MSISs) are generally studied from the utility point of view, which may cause two problems: 1) the objects are strictly classified into good or bad, which may lead to misclassification and 2) the risk attitude and psychological behaviors of decision makers are difficult to be reflected. In light of this, this article proposes a wide three-way decision (3WD) model on an MSIS, which combines 3WD theory and regret theory and can precisely make up for these two shortcomings. First, by virtue of regret theory, an outranking relation on the comprehensive MSIS is constructed according to the regret-rejoicing index. Second, objects in the outranking relation are classified into three different domains by a clustering method. In each domain, the ranking of objects can be calculated by using the relative closeness coefficient. Finally, we use the cases in the database to simulate the experiment to verify the decision-making effect of the proposed model. Comparative analysis and experimental analysis also show the effectiveness, superiority, and stability of the proposed model.
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3
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Xu Y, Dai W, Huang J, Li M, Herrera-Viedma E. Corrigendum to “Some models to manage additive consistency and derive priority weights from hesitant fuzzy preference relations” [Inform. Sci. 586 (2022) 450–467]. Inf Sci (N Y) 2023. [DOI: 10.1016/j.ins.2023.02.075] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/06/2023]
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4
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Wu J, Zhang G, Xing Y, Liu Y, Zhang Z, Dong Y, Herrera-Viedma E. A sentiment analysis driven method based on public and personal preferences with correlated attributes to select online doctors. APPL INTELL 2023; 53:1-22. [PMID: 36844914 PMCID: PMC9940095 DOI: 10.1007/s10489-023-04485-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/23/2023] [Indexed: 02/25/2023]
Abstract
This paper proposes a method to assist patients in finding the most appropriate doctor for online medical consultation. To do that, it constructs an online doctor selection decision-making method that considers the correlation attributes, in which the measure of attribute correlation is derived from the history real decision data. To combine public and personal preference with correlated attributes, it proposes a Choquet integral based comprehensive online doctor ranking method. In detail, a two stage classification model based on BERT (Bidirectional Encoder Representations from Transformers) is used to extract service features from unstructured text reviews. Then, 2-additive fuzzy measure is adopted to represent the patient public group aggregated attribute preference. Next, a novel optimization model is proposed to combine the public preference and personal preference. Finally, a case study of dxy.com is carried out to illustrate the procedure of the method. The comparison result between proposed method and other traditional MADM (multi-attribute decision-making) methods prove its rationality.
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Affiliation(s)
- Jian Wu
- School of Economics and Management, Shanghai Maritime University, Shanghai, 201306 China
- Center for Artificial Intelligence and Decision Sciences, Shanghai Maritime University, Shanghai, 201306 China
| | - Guangyin Zhang
- School of Economics and Management, Shanghai Maritime University, Shanghai, 201306 China
- Center for Artificial Intelligence and Decision Sciences, Shanghai Maritime University, Shanghai, 201306 China
| | - Yumei Xing
- School of Economics and Management, Shanghai Maritime University, Shanghai, 201306 China
- Center for Artificial Intelligence and Decision Sciences, Shanghai Maritime University, Shanghai, 201306 China
| | - Yujia Liu
- School of Economics and Management, Shanghai Maritime University, Shanghai, 201306 China
- Center for Artificial Intelligence and Decision Sciences, Shanghai Maritime University, Shanghai, 201306 China
| | - Zhen Zhang
- Institute of Systems Engineering, Dalian University of Technology, Dalian, 116024 China
| | - Yucheng Dong
- Business School, Sichuan University, Chengdu, 610065 China
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5
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Das SK, Dey N, González Crespo R, Herrera-Viedma E. A Non-Linear Multi-Objective Technique for Hybrid Peer-to-Peer Communication. Inf Sci (N Y) 2023. [DOI: 10.1016/j.ins.2023.01.117] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
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6
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Hallaji E, Razavi-Far R, Saif M, Herrera-Viedma E. Label noise analysis meets adversarial training: A defense against label poisoning in federated learning. Knowl Based Syst 2023. [DOI: 10.1016/j.knosys.2023.110384] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/16/2023]
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7
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Liu X, Zhang Y, Xu Y, Li M, Herrera-Viedma E. A consensus model for group decision-making with personalized individual self-confidence and trust semantics: A perspective on dynamic social network interactions. Inf Sci (N Y) 2023. [DOI: 10.1016/j.ins.2023.01.087] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/19/2023]
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8
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Sun Q, Wu J, Chiclana F, Wang S, Herrera-Viedma E, Yager RR. An approach to prevent weight manipulation by minimum adjustment and maximum entropy method in social network group decision making. Artif Intell Rev 2022; 56:7315-7346. [PMID: 36532202 PMCID: PMC9746597 DOI: 10.1007/s10462-022-10361-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
In social network group decision making (SN-GDM) problem, subgroup weights are mostly unknown, many approaches have been proposed to determine the subgroup weights. However, most of these methods ignore the weight manipulation behavior of subgroups. Some studies indicated that weight manipulation behavior hinders consensus efficiency. To deal with this issue, this paper proposes a theoretical framework to prevent weight manipulation in SN-GDM. Firstly, a community detection based method is used to cluster the large group. The power relations of subgroups are measured by the power index (PI), which depends on the subgroups size and cohesion. Then, a minimum adjustment feedback model with maximum entropy is proposed to prevent subgroups' manipulation behavior. The minimum adjustment rule aims for 'efficiency' while the maximum entropy rule aims for 'justice'. The experimental results show that the proposed model can guarantee the rationality of weight distribution to reach consensus efficiently, which is achieved by maintaining a balance between 'efficiency' and 'justice' in the mechanism of assigning weights. Finally, the detailed numerical and simulation analyses are carried out to verify the validity of the proposed method.
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Affiliation(s)
- Qi Sun
- School of Economics and Management, Shanghai Maritime University, Shanghai, 201306 China
- Center for Artificial Intelligence and Decision Sciences, Shanghai Maritime University, Shanghai, 201306 China
| | - Jian Wu
- School of Economics and Management, Shanghai Maritime University, Shanghai, 201306 China
- Center for Artificial Intelligence and Decision Sciences, Shanghai Maritime University, Shanghai, 201306 China
| | - Francisco Chiclana
- Faculty of Computing, Engineering and Media, Institute of Artificial Intelligence, De Montfort University, Leicester, UK
- Department of Computer Science and AI, Andalusian Research Institute in Data Science and Computational Intelligence, University of Granada, 18071 Granada, Spain
| | - Sha Wang
- School of Economics and Management, Shanghai Maritime University, Shanghai, 201306 China
- Center for Artificial Intelligence and Decision Sciences, Shanghai Maritime University, Shanghai, 201306 China
| | - Enrique Herrera-Viedma
- Department of Computer Science and AI, Andalusian Research Institute in Data Science and Computational Intelligence, University of Granada, 18071 Granada, Spain
- Department of Electrical and Computer Engineering, Faculty of Engineering, King Abdulaziz University, Jeddah, 21589 Saudi Arabia
| | - Ronald R. Yager
- Machine Intelligence Institute, Iona College, New Rochelle, NY 10801 USA
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Li X, Xu Z, Wang H, Herrera-Viedma E, Taylan O. Classification of the wind turbine components based on importance degrees: A three-way decision perspective. Appl Soft Comput 2022. [DOI: 10.1016/j.asoc.2022.109754] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
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10
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Ma X, Gong Z, Wei G, Herrera-Viedma E. A New Consensus Model Based on Trust Interactive Weights for Intuitionistic Group Decision Making in Social Networks. IEEE Trans Cybern 2022; 52:13106-13119. [PMID: 34415844 DOI: 10.1109/tcyb.2021.3100849] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
A promising feature for group decision making (GDM) lies in the study of the interaction between individuals. In conventional GDM research, experts are independent. This is reflected in the setting of preferences and weights. Nevertheless, each expert's role is played through communication, collaboration, and cooperation with other individuals. The interaction from others may affect the power of an expert as well as his/her opinion. Furthermore, it is noted that a link path with the highest degree of trust is the most efficient information transmission channel. Inspired by these findings, an optimal trust-induced consensus process is designed with the usage of intuitionistic fuzzy preference relation. The comprehensive weight of each expert is decomposed into two portions, namely: 1) the individual weights and 2) interactive weights. Three optimization models are constructed to achieve weight parameters under different decision situations, where the weight parameters are represented through a 2-order additive fuzzy measure and the Shapley value. To reflect the interaction, the Choquet integral is employed for aggregating opinions, and a novel distance measure is adopted for accomplishing a consensus index. An illustrative example and comparison are put in practice to show the effectiveness and improvements of the proposed method.
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Morente-Molinera J, Morfeq A, Al-Hmouz R, Ashary E, Su J, Herrera-Viedma E. Introducing disruption on stagnated Group Decision Making processes using Fuzzy Ontologies. Appl Soft Comput 2022. [DOI: 10.1016/j.asoc.2022.109868] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
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12
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Li CC, Liang H, Dong Y, Chiclana F, Herrera-Viedma E. Consistency Improvement With a Feedback Recommendation in Personalized Linguistic Group Decision Making. IEEE Trans Cybern 2022; 52:10052-10063. [PMID: 34191738 DOI: 10.1109/tcyb.2021.3085760] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
Consistency is an important issue in linguistic decision making with various consistency measures and consistency improving methods available in the literature. However, existing linguistic consistency studies omit the fact that words mean different things for different people, that is, decision makers' personalized individual semantics (PISs) over their expressed linguistic preferences are ignored. Therefore, the aim of this article is to propose a novel consistency improving approach based on PISs in linguistic group decision making. The proposed approach combines the characteristics of personalized representation and integrates the PIS-based model in measuring and improving the consistency of linguistic preference relations. A detailed numerical and comparative analysis to support the feasibility of the proposed approach is provided.
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Wu J, Wang S, Chiclana F, Herrera-Viedma E. Two-Fold Personalized Feedback Mechanism for Social Network Consensus by Uninorm Interval Trust Propagation. IEEE Trans Cybern 2022; 52:11081-11092. [PMID: 34003760 DOI: 10.1109/tcyb.2021.3076420] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
A two-fold personalized feedback mechanism is established for consensus reaching in social network group decision-making (SN-GDM). It consists of two stages: 1) generating the trusted recommendation advice for individuals and 2) producing a a personalized adoption coefficient for reducing unnecessary adjustment costs. A uninorm interval-valued trust propagation operator is developed to obtain an indirect trust relationship, which is used to generate personalized recommendation advice based on the principle of "a recommendation being more acceptable the higher the level of trust it derives from." An optimization model is built to minimize the total adjustment cost of reaching consensus by determining the personalized feedback adoption coefficient based on individuals' consensus levels. Consequently, the proposed two-fold personalized feedback mechanism achieves a balance between group consensus and individual personality. An example to demonstrate how the proposed two-fold personalized feedback mechanism works is included, which is also used to show its rationality by comparing it with the traditional feedback mechanism in group decision making (GDM).
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14
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Wang W, Zhan J, Herrera-Viedma E. A three-way decision approach with a probability dominance relation based on prospect theory for incomplete information systems. Inf Sci (N Y) 2022. [DOI: 10.1016/j.ins.2022.08.065] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
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15
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Zhan M, Kou G, Dong Y, Chiclana F, Herrera-Viedma E. Bounded Confidence Evolution of Opinions and Actions in Social Networks. IEEE Trans Cybern 2022; 52:7017-7028. [PMID: 33449900 DOI: 10.1109/tcyb.2020.3043635] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
Inspired by the continuous opinion and discrete action (CODA) model, bounded confidence and social networks, the bounded confidence evolution of opinions and actions in social networks is investigated and a social network opinions and actions evolutions (SNOAEs) model is proposed. In the SNOAE model, it is assumed that each agent has a CODA for a certain issue. Agents' opinions are private and invisible, that is, an individual agent only knows its own opinion and cannot obtain other agents' opinions unless there is a social network connection edge that allows their communication; agents' actions are public and visible to all agents and impact other agents' actions. Opinions and actions evolve in a directed social network. In the limitation of the bounded confidence, other agents' actions or agents' opinions noticed or obtained by network communication, respectively, are used by agents to update their opinions. Based on the SNOAE model, the evolution of the opinions and actions with bounded confidence is investigated in social networks both theoretically and experimentally with a detailed simulation analysis. Theoretical research results show that discrete actions can attract agents who trust the discrete action, and make agents to express extreme opinions. Simulation experiments results show that social network connection probability, bounded confidence, and the opinion threshold of action choice parameters have strong impacts on the evolution of opinions and actions. However, the number of agents in the social network has no obvious influence on the evolution of opinions and actions.
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Herrera-Viedma E, Chiclana F, Dong Y, Peng Y, Xu Y, Cabrerizo FJ. Special issue on Soft Computing based Intelligent Decision Making Systems for Dynamic Frameworks with Real-world Application. Appl Soft Comput 2022. [DOI: 10.1016/j.asoc.2022.109059] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/02/2022]
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17
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Lu Y, Xu Y, Herrera-Viedma E. Consensus progress for large-scale group decision making in social networks with incomplete probabilistic hesitant fuzzy information. Appl Soft Comput 2022. [DOI: 10.1016/j.asoc.2022.109249] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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18
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Hassani H, Razavi-Far R, Saif M, Herrera-Viedma E. Consensus-Based Decision Support Model and Fusion Architecture for Dynamic Decision Making. Inf Sci (N Y) 2022. [DOI: 10.1016/j.ins.2022.03.040] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/17/2023]
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19
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Abolghasemi R, Engelstad P, Herrera-Viedma E, Yazidi A. A personality-aware group recommendation system based on pairwise preferences. Inf Sci (N Y) 2022. [DOI: 10.1016/j.ins.2022.02.033] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
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20
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Bueno I, Carrasco RA, Ureña R, Herrera-Viedma E. A business context aware decision-making approach for selecting the most appropriate sentiment analysis technique in e-marketing situations. Inf Sci (N Y) 2022. [DOI: 10.1016/j.ins.2021.12.080] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/01/2022]
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21
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Xu Y, Zhu S, Liu X, Huang J, Herrera-Viedma E. Additive consistency exploration of linguistic preference relations with self-confidence. Artif Intell Rev 2022. [DOI: 10.1007/s10462-022-10172-x] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/02/2022]
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22
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Xu Y, Dai W, Huang J, Li M, Herrera-Viedma E. Some models to manage additive consistency and derive priority weights from hesitant fuzzy preference relations. Inf Sci (N Y) 2022. [DOI: 10.1016/j.ins.2021.12.002] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
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23
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Zhang JW, Liu F, Tu HN, Herrera-Viedma E. A decision-making model with sequential incomplete additive pairwise comparisons. Knowl Based Syst 2022. [DOI: 10.1016/j.knosys.2021.107766] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
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24
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Yazidi A, Pinto-Orellana MA, Hammer H, Mirtaheri P, Herrera-Viedma E. Solving Sensor Identification Problem Without Knowledge of the Ground Truth Using Replicator Dynamics. IEEE Trans Cybern 2022; 52:16-24. [PMID: 31905160 DOI: 10.1109/tcyb.2019.2958627] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
In this article, we consider an emergent problem in the sensor fusion area in which unreliable sensors need to be identified in the absence of the ground truth. We devise a novel solution to the problem using the theory of replicator dynamics that require mild conditions compared to the available state-of-the-art approaches. The solution has a low computational complexity that is linear in terms of the number of involved sensors. We provide some sound theoretical results that catalog the convergence of our approach to a solution where we can clearly unveil the sensor type. Furthermore, we present some experimental results that demonstrate the convergence of our approach in concordance with our theoretical findings.
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25
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Zhou M, Hu M, Chen YW, Cheng BY, Wu J, Herrera-Viedma E. Towards achieving consistent opinion fusion in group decision making with complete distributed preference relations. Knowl Based Syst 2022. [DOI: 10.1016/j.knosys.2021.107740] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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26
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Xu Y, Gong Z, Forrest JYL, Herrera-Viedma E. Trust propagation and trust network evaluation in social networks based on uncertainty theory. Knowl Based Syst 2021. [DOI: 10.1016/j.knosys.2021.107610] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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27
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Tang M, Liao H, Herrera-Viedma E, Chen CLP, Pedrycz W. A Dynamic Adaptive Subgroup-to-Subgroup Compatibility-Based Conflict Detection and Resolution Model for Multicriteria Large-Scale Group Decision Making. IEEE Trans Cybern 2021; 51:4784-4795. [PMID: 32149679 DOI: 10.1109/tcyb.2020.2974924] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
The current societal demands and technological developments have resulted in the participation of a large number of experts in making decisions as a group. Conflicts are imminent in groups and conflict management is complex and necessary especially in a large group. However, there are few studies that quantitatively research the conflict detection and resolution in the large-group context, especially in the multicriteria large-group decision making (GDM) context. This article proposes a dynamic adaptive subgroup-to-subgroup conflict model to solve multicriteria large-scale GDM problems. A compatibility index is proposed based on two kinds of conflicts among experts: 1) cognitive conflict and 2) interest conflict. Then, the fuzzy c -means clustering algorithm is used to classify experts into several subgroups. A subgroup-to-subgroup conflict detection method and a weight-determination approach are developed based on the clustering results. Afterward, a conflict resolution model, which can dynamically generate feedback suggestion, is introduced. Finally, an illustrative example is provided to demonstrate the effectiveness and applicability of the proposed model.
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Zhou W, Liu M, Xu Z, Herrera-Viedma E. Global fusion of multiple order relations and hesitant fuzzy decision analysis. APPL INTELL 2021. [DOI: 10.1007/s10489-021-02689-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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29
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Morente-Molinera J, Kou G, Samuylov K, Cabrerizo F, Herrera-Viedma E. Using argumentation in expert’s debate to analyze multi-criteria group decision making method results. Inf Sci (N Y) 2021. [DOI: 10.1016/j.ins.2021.05.086] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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30
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Seiti H, Fathi M, Hafezalkotob A, Herrera-Viedma E, Hameed IA. Developing the modified R-numbers for risk-based fuzzy information fusion and its application to failure modes, effects, and system resilience analysis (FMESRA). ISA Trans 2021; 113:9-27. [PMID: 32005404 DOI: 10.1016/j.isatra.2020.01.015] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/13/2019] [Revised: 11/24/2019] [Accepted: 01/08/2020] [Indexed: 06/10/2023]
Abstract
In order to identify and eliminate known or potential failures from the process of product design, development and production, failure mode and effect analysis (FMEA) have been widely used in a variety of industries as a useful tool in prognostics and health management, safety and reliability analysis. The traditional FMEA shows two significant flaws while calculating the risk priority number (RPN). First, recovery time that considerably affects the safety, cost, and sustainability of the system is not considered in the RPN calculation. Second, in order to capture different conflicting experts' views, especially when the obtained data are fuzzy, there is no mechanism. In order to overcome these issues, this paper presents a resilience-based risk priority number for considering the recovery and repair time of each failure mode, then a risk-based fuzzy information processing and decision-making is developed by modifying the R-numbers methodology and on the basis of simultaneous evaluation of criteria and alternatives (SECA) approach which is so-called R-SECA method. The capability of proposed models is tested by a case study of a centrifugal air compressor in a steel manufacturing company. Results show the robustness of proposed R-SECA model in dealing with different scenarios of risky information.
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Affiliation(s)
- Hamidreza Seiti
- Department of Industrial Engineering, Science and Research Branch, Islamic Azad University Tehran, Iran.
| | - Mahdi Fathi
- Department of Management, Dehdasht Branch, Islamic Azad University, Dehdasht, Iran
| | - Ashkan Hafezalkotob
- College of Industrial Engineering, Islamic Azad University, South Tehran Branch, Tehran, Iran
| | - Enrique Herrera-Viedma
- Andalusian Research Institute in Data Science and Computational Intelligence, University of Granada, Granada 18071, Spain; Department of Electrical and Computer Engineering, Faculty of Engineering, King Abdulaziz University, Jeddah 21589, Saudi Arabia
| | - Ibrahim A Hameed
- Department of ICT and Natural Sciences, Norwegian University of Science and Technology, 6009 Å lesund, Norway
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Guo W, Gong Z, Herrera-Viedma E, Li Q. Priority weights acquisition of linear uncertain preference relations and its application in the ranking of online shopping platforms. Appl Soft Comput 2021. [DOI: 10.1016/j.asoc.2021.107292] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
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32
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Liu XX, Hu S, Fong SJ, Crespo RG, Herrera-Viedma E. Modelling dynamics of coronavirus disease 2019 spread for pandemic forecasting based on Simulink. Phys Biol 2021; 18. [PMID: 33873177 DOI: 10.1088/1478-3975/abf990] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2020] [Accepted: 04/19/2021] [Indexed: 11/12/2022]
Abstract
In this paper, we demonstrate the application of MATLAB to develop a pandemic prediction system based on Simulink. The susceptible-exposed-asymptomatic but infectious-symptomatic and infectious (severe infected population + mild infected population)-recovered-deceased (SEAI(I1+I2)RD) physical model for unsupervised learning and two types of supervised learning, namely, fuzzy proportional-integral-derivative (PID) and wavelet neural-network PID learning, are used to build a predictive-control system model that enables self-learning artificial intelligence (AI)-based control. After parameter setting, the data entering the model are predicted, and the value of the data set at a future moment is calculated. PID controllers are added to ensure that the system does not diverge at the beginning of iterative learning. To adapt to complex system conditions and afford excellent control, a wavelet neural-network PID control strategy is developed that can be adjusted and corrected in real time, according to the output error.
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Affiliation(s)
- Xian-Xian Liu
- Department of Computer and Information Science, University of Macau, Macau SAR, China
| | - Shimin Hu
- Department of Computer and Information Science, University of Macau, Macau SAR, China
| | - Simon James Fong
- Department of Computer and Information Science, University of Macau, Macau SAR, China
| | - Rubén González Crespo
- Computer Science and Technology Department, Universidad Internacional de La Rioja, La Rioja, Logroño, Spain
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Sánchez-Núñez P, Cobo MJ, Vaccaro G, Peláez JI, Herrera-Viedma E. Citation Classics in Consumer Neuroscience, Neuromarketing and Neuroaesthetics: Identification and Conceptual Analysis. Brain Sci 2021; 11:548. [PMID: 33925436 PMCID: PMC8146570 DOI: 10.3390/brainsci11050548] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2021] [Revised: 04/22/2021] [Accepted: 04/23/2021] [Indexed: 11/16/2022] Open
Abstract
Neuromarketing, consumer neuroscience and neuroaesthetics are a broad research area of neuroscience with an extensive background in scientific publications. Thus, the present study aims to identify the highly cited papers (HCPs) in this research field, to deliver a summary of the academic work produced during the last decade in this area, and to show patterns, features, and trends that define the past, present, and future of this specific area of knowledge. The HCPs show a perspective of those documents that, historically, have attracted great interest from a research community and that could be considered as the basis of the research field. In this study, we retrieved 907 documents and analyzed, through H-Classics methodology, 50 HCPs identified in the Web of Science (WoS) during the period 2010-2019. The H-Classic approach offers an objective method to identify core knowledge in neuroscience disciplines such as neuromarketing, consumer neuroscience, and neuroaesthetics. To accomplish this study, we used Bibliometrix R Package and SciMAT software. This analysis provides results that give us a useful insight into the development of this field of research, revealing those scientific actors who have made the greatest contribution to its development: authors, institutions, sources, countries as well as documents and references.
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Affiliation(s)
- Pablo Sánchez-Núñez
- Joint-PhD Programme in Communication, Department of Audiovisual Communication and Advertising, Faculty of Communication Sciences, Universidad de Málaga, 29071 Málaga, Spain
- Center for Applied Social Research (CISA), Universidad de Málaga, 29071 Málaga, Spain; (G.V.); (J.I.P.)
- Instituto de Investigación Biomédica de Málaga (IBIMA), 29010 Málaga, Spain
| | - Manuel J. Cobo
- Department of Computer Science and Engineering, School of Engineering, Universidad de Cádiz, 11202 Cádiz, Spain;
| | - Gustavo Vaccaro
- Center for Applied Social Research (CISA), Universidad de Málaga, 29071 Málaga, Spain; (G.V.); (J.I.P.)
- Instituto de Investigación Biomédica de Málaga (IBIMA), 29010 Málaga, Spain
- Department of Languages and Computer Science, Higher Technical School of Computer Engineering, Universidad de Málaga, 29071 Málaga, Spain
| | - José Ignacio Peláez
- Center for Applied Social Research (CISA), Universidad de Málaga, 29071 Málaga, Spain; (G.V.); (J.I.P.)
- Instituto de Investigación Biomédica de Málaga (IBIMA), 29010 Málaga, Spain
- Department of Languages and Computer Science, Higher Technical School of Computer Engineering, Universidad de Málaga, 29071 Málaga, Spain
| | - Enrique Herrera-Viedma
- Andalusian Research Institute on Data Science and Computational Intelligence, Department of Computer Science and AI, University of Granada, 18071 Granada, Spain;
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Bueno I, Carrasco RA, Porcel C, Kou G, Herrera-Viedma E. A linguistic multi-criteria decision making methodology for the evaluation of tourist services considering customer opinion value. Appl Soft Comput 2021. [DOI: 10.1016/j.asoc.2020.107045] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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Liu XX, Fong SJ, Dey N, Crespo RG, Herrera-Viedma E. A new SEAIRD pandemic prediction model with clinical and epidemiological data analysis on COVID-19 outbreak. APPL INTELL 2021; 51:4162-4198. [PMID: 34764574 PMCID: PMC7775669 DOI: 10.1007/s10489-020-01938-3] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/11/2020] [Indexed: 02/07/2023]
Abstract
Measuring the spread of disease during a pandemic is critically important for accurately and promptly applying various lockdown strategies, so to prevent the collapse of the medical system. The latest pandemic of COVID-19 that hits the world death tolls and economy loss very hard, is more complex and contagious than its precedent diseases. The complexity comes mostly from the emergence of asymptomatic patients and relapse of the recovered patients which were not commonly seen during SARS outbreaks. These new characteristics pertaining to COVID-19 were only discovered lately, adding a level of uncertainty to the traditional SEIR models. The contribution of this paper is that for the COVID-19 epidemic, which is infectious in both the incubation period and the onset period, we use neural networks to learn from the actual data of the epidemic to obtain optimal parameters, thereby establishing a nonlinear, self-adaptive dynamic coefficient infectious disease prediction model. On the basis of prediction, we considered control measures and simulated the effects of different control measures and different strengths of the control measures. The epidemic control is predicted as a continuous change process, and the epidemic development and control are integrated to simulate and forecast. Decision-making departments make optimal choices. The improved model is applied to simulate the COVID-19 epidemic in the United States, and by comparing the prediction results with the traditional SEIR model, SEAIRD model and adaptive SEAIRD model, it is found that the adaptive SEAIRD model's prediction results of the U.S. COVID-19 epidemic data are in good agreement with the actual epidemic curve. For example, from the prediction effect of these 3 different models on accumulative confirmed cases, in terms of goodness of fit, adaptive SEAIRD model (0.99997) ≈ SEAIRD model (0.98548) > Classical SEIR model (0.66837); in terms of error value: adaptive SEAIRD model (198.6563) < < SEAIRD model(4739.8577) < < Classical SEIR model (22,652.796); The objective of this contribution is mainly on extending the current spread prediction model. It incorporates extra compartments accounting for the new features of COVID-19, and fine-tunes the new model with neural network, in a bid of achieving a higher level of prediction accuracy. Based on the SEIR model of disease transmission, an adaptive model called SEAIRD with internal source and isolation intervention is proposed. It simulates the effects of the changing behaviour of the SARS-CoV-2 in U.S. Neural network is applied to achieve a better fit in SEAIRD. Unlike the SEIR model, the adaptive SEAIRD model embraces multi-group dynamics which lead to different evolutionary trends during the epidemic. Through the risk assessment indicators of the adaptive SEAIRD model, it is convenient to measure the severity of the epidemic situation for consideration of different preventive measures. Future scenarios are projected from the trends of various indicators by running the adaptive SEAIRD model.
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Affiliation(s)
- Xian-Xian Liu
- Department of Computer and Information Science, University of Macau, SAR, Macau, China
| | - Simon James Fong
- Department of Computer and Information Science, University of Macau, SAR, Macau, China ,DACC Laboratory, Zhuhai Institutes of Advanced Technology of the Chinese Academy of Sciences, Zhuhai, China
| | - Nilanjan Dey
- Department of Computer Science and Engineering, JIS University, Kolkata, India
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Chan Chiu P, Selamat A, Krejcar O, Kuok Kuok K, Herrera-Viedma E, Fenza G. Imputation of Rainfall Data Using the Sine Cosine Function Fitting Neural Network. IJIMAI 2021. [DOI: 10.9781/ijimai.2021.08.013] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
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Seal A, Karlekar A, Krejcar O, Herrera-Viedma E. Performance and Convergence Analysis of Modified C-Means Using Jeffreys-Divergence for Clustering. IJIMAI 2021. [DOI: 10.9781/ijimai.2021.04.009] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
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Xie W, Xu Z, Ren Z, Herrera-Viedma E. The probe for the weighted dual probabilistic linguistic correlation coefficient to invest an artificial intelligence project. Soft comput 2020. [DOI: 10.1007/s00500-020-04873-0] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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Ijadi Maghsoodi A, Soudian S, Martínez L, Herrera-Viedma E, Zavadskas EK. A phase change material selection using the interval-valued target-based BWM-CoCoMULTIMOORA approach: A case-study on interior building applications. Appl Soft Comput 2020. [DOI: 10.1016/j.asoc.2020.106508] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
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Lu Y, Xu Y, Herrera-Viedma E, Han Y. Consensus of large-scale group decision making in social network: the minimum cost model based on robust optimization. Inf Sci (N Y) 2020; 547:910-930. [PMID: 32904482 PMCID: PMC7456267 DOI: 10.1016/j.ins.2020.08.022] [Citation(s) in RCA: 50] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2020] [Revised: 07/29/2020] [Accepted: 08/07/2020] [Indexed: 11/17/2022]
Abstract
The minimum cost consensus model is proposed to coordinate the opinions of experts. A new method of LSGDM clustering is proposed to improve CRP efficiency. A consensus index CI reflecting the harmony degree between experts is devised. A robust counterpart of robust optimization consensus is implemented.
Recently, large-scale group decision making (LSGDM) in social network comes into being. In the practical consensus of LSGDM, the unit adjustment cost of experts is difficult to obtain and may be uncertain. Therefore, the purpose of this paper is to propose a consensus model based on robust optimization. This paper focuses on LSGDM, considering the social relationship between experts. In the presented model, an expert clustering method, combining trust degree and relationship strength, is used to classify experts with similar opinions into subgroups. A consensus index, reflecting the harmony degree between experts, is devised to measure the consensus level among experts. Then, a minimum cost model based on robust optimization is proposed to solve the robust optimization consensus problem. Subsequently, a detailed consensus feedback adjustment is presented. Finally, a case study and comparative analysis are provided to verify the validity and advantage of the proposed method.
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Affiliation(s)
- Yanling Lu
- Business School, Hohai University, Nanjing 211100, China
| | - Yejun Xu
- Business School, Hohai University, Nanjing 211100, China
| | - Enrique Herrera-Viedma
- Andalusian Research Institute in Data Science and Computational Intelligence, University of Granada, Granada 18071, Spain.,Peoples' Friendship University of Russia (RUDN University), Moscow, Russian Federation
| | - Yefan Han
- Business school, University of Shanghai for Science and Technology, Shanghai, China
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Panigrahy C, Seal A, Kumar Mahato N, Krejcar O, Herrera-Viedma E. Multi-focus image fusion using fractal dimension: publisher's note. Appl Opt 2020; 59:6593. [PMID: 32749359 DOI: 10.1364/ao.401583] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/29/2020] [Indexed: 06/11/2023]
Abstract
This publisher's note amends information in the Funding section of Appl. Opt.59, 5642 (2020).APOPAI0003-693510.1364/AO.391234.
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Seiti H, Hafezalkotob A, Herrera-Viedma E. A novel linguistic approach for multi-granular information fusion and decision-making using risk-based linguistic D numbers. Inf Sci (N Y) 2020. [DOI: 10.1016/j.ins.2020.04.006] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
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Panigrahy C, Seal A, Kumar Mahato N, Krejcar O, Herrera-Viedma E. Multi-focus image fusion using fractal dimension. Appl Opt 2020; 59:5642-5655. [PMID: 32609685 DOI: 10.1364/ao.391234] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/24/2020] [Accepted: 05/27/2020] [Indexed: 06/11/2023]
Abstract
Multi-focus image fusion is defined as "the combination of a group of partially focused images of a same scene with the objective of producing a fully focused image." Normally, transform-domain-based image fusion methods preserve the textures and edges in the blend image, but many are translation variant. The translation-invariant transforms produce the same size approximation and detail images, which are more convenient to devise the fusion rules. In this work, a translation-invariant multi-focus image fusion approach using the à-trous wavelet transform is introduced, which uses fractal dimension as a clarity measure for the approximation coefficients and Otsu's threshold to fuse the detail coefficients. The subjective assessment of the proposed method is carried out using the fusion results of nine state-of-the-art methods. On the other hand, eight fusion quality metrics are considered for the objective assessment. The results of subjective and objective assessment on grayscale and color multi-focus image pairs illustrate that the proposed method is competitive and even better than some of the existing methods.
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Lázaro-Rodríguez P, López-Gijón J, Alonso S, Herrera-Viedma E. Actualidad en estudios LibQUAL+®: paradigmas de la biblioteca informativa y social-creadora y cuestión de género como reflejos de la realidad social. Rev esp doc cient 2020. [DOI: 10.3989/redc.2020.2.1649] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022] Open
Abstract
Los objetivos de este artículo son cuatro: analizar las principales diferencias en torno a las dimensiones mejor valoradas de tres estudios sobre satisfacción de personas usuarias basados en LibQUAL+® llevados a cabo en bibliotecas universitarias de España, Argentina y Chile; analizar las diferencias atendiendo a la variable de género (hombres y mujeres); determinar si las diferencias en cuanto a género son estadísticamente significativas; y discutir y reflexionar sobre los resultados hallados en el ámbito concreto de las bibliotecas como reflejo de la realidad social en general. Los resultados permiten concluir que en España las personas usuarias están menos satisfechas con la dimensión de la biblioteca como espacio, mientras que en Latinoamericana se percibe menor grado de satisfacción también con el control de la información. El mayor grado de satisfacción en todos los estudios se da en el valor afectivo del servicio. Las mujeres en España muestran menor satisfacción y mayor exigencia que los hombres en el valor afectivo del servicio. Además, se hallaron diferencias estadísticamente significativas en el análisis de las medias por género. En la discusión se ponen en relación los resultados hallados con la literatura existente, definiendo los paradigmas posibles de la biblioteca informativa frente al de la social-creadora y la percepción de la satisfacción por géneros según el contexto social en que se hallan las bibliotecas. La limitación principal del artículo es que se basa en tres estudios concretos; y su principal valor y originalidad, que puede considerarse como punto de partida para futuras investigaciones sobre la cuestión de género en lo que a bibliotecas y los servicios que ofrecen se refiere.
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Xie W, Xu Z, Ren Z, Herrera-Viedma E. A new multi-criteria decision model based on incomplete dual probabilistic linguistic preference relations. Appl Soft Comput 2020. [DOI: 10.1016/j.asoc.2020.106237] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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Alfaro-García VG, Merigó JM, Alfaro Calderón GG, Plata-Pérez L, Gil-Lafuente AM, Herrera-Viedma E. A citation analysis of fuzzy research by universities and countries. IFS 2020. [DOI: 10.3233/jifs-179629] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Affiliation(s)
- Victor G. Alfaro-García
- Facultad de Contaduría y Ciencias Administrativas, Universidad Michoacana de San Nicolás de Hidalgo, Morelia, México
| | - José M. Merigó
- Department of Management Control and Information Systems, School of Economics and Business, University of Chile, Santiago, Chile
- School of Information, Systems and Modelling, University of Technology Sydney, NSW, Australia
| | - Gerardo G. Alfaro Calderón
- Facultad de Contaduría y Ciencias Administrativas, Universidad Michoacana de San Nicolás de Hidalgo, Morelia, México
| | - Leobardo Plata-Pérez
- Facultad de Economia, Universidad Autónoma de San Luis Potosí, San Luis Potosí, México
| | | | - Enrique Herrera-Viedma
- Andalusian Research Institute on Data Science and Computational Intelligence, University of Granada, Granada, Spain
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Morente-Molinera J, Cabrerizo F, Mezei J, Carlsson C, Herrera-Viedma E. A dynamic group decision making process for high number of alternatives using hesitant Fuzzy Ontologies and sentiment analysis. Knowl Based Syst 2020. [DOI: 10.1016/j.knosys.2020.105657] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
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Fong SJ, Li G, Dey N, Crespo RG, Herrera-Viedma E. Composite Monte Carlo decision making under high uncertainty of novel coronavirus epidemic using hybridized deep learning and fuzzy rule induction. Appl Soft Comput 2020; 93:106282. [PMID: 32362799 PMCID: PMC7195106 DOI: 10.1016/j.asoc.2020.106282] [Citation(s) in RCA: 124] [Impact Index Per Article: 31.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2020] [Revised: 04/03/2020] [Accepted: 04/07/2020] [Indexed: 11/27/2022]
Abstract
In the advent of the novel coronavirus epidemic since December 2019, governments and authorities have been struggling to make critical decisions under high uncertainty at their best efforts. In computer science, this represents a typical problem of machine learning over incomplete or limited data in early epidemic Composite Monte-Carlo (CMC) simulation is a forecasting method which extrapolates available data which are broken down from multiple correlated/casual micro-data sources into many possible future outcomes by drawing random samples from some probability distributions. For instance, the overall trend and propagation of the infested cases in China are influenced by the temporal–spatial data of the nearby cities around the Wuhan city (where the virus is originated from), in terms of the population density, travel mobility, medical resources such as hospital beds and the timeliness of quarantine control in each city etc. Hence a CMC is reliable only up to the closeness of the underlying statistical distribution of a CMC, that is supposed to represent the behaviour of the future events, and the correctness of the composite data relationships. In this paper, a case study of using CMC that is enhanced by deep learning network and fuzzy rule induction for gaining better stochastic insights about the epidemic development is experimented. Instead of applying simplistic and uniform assumptions for a MC which is a common practice, a deep learning-based CMC is used in conjunction of fuzzy rule induction techniques. As a result, decision makers are benefited from a better fitted MC outputs complemented by min–max rules that foretell about the extreme ranges of future possibilities with respect to the epidemic. Composite Monte-Carlo (CMC) simulation is a forecasting method. A case study of using CMC through deep learning network is developed. Decision makers are benefited from a better fitted Monte Carlo outputs. Novel Coronavirus Epidemic is studied.
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Affiliation(s)
- Simon James Fong
- Department of Computer and Information Science, University of Macau, Macau, SAR, China
- DACC Laboratory, Zhuhai Institutes of Advanced Technology of the Chinese Academy of Sciences, China
- Corresponding author at: Department of Computer and Information Science, University of Macau, Macau, SAR, China.
| | - Gloria Li
- DACC Laboratory, Zhuhai Institutes of Advanced Technology of the Chinese Academy of Sciences, China
| | - Nilanjan Dey
- Department of Information Technology, Techno India College of Technology, India
- Corresponding author.
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Abstract
BACKGROUND In biomedicine, infrared thermography is the most promising technique among other conventional methods for revealing the differences in skin temperature, resulting from the irregular temperature dispersion, which is the significant signaling of diseases and disorders in human body. Given the process of detecting emitted thermal radiation of human body temperature by infrared imaging, we, in this study, present the current utility of thermal camera models namely FLIR and SEEK in biomedical applications as an extension of our previous article. RESULTS The most significant result is the differences between image qualities of the thermograms captured by thermal camera models. In other words, the image quality of the thermal images in FLIR One is higher than SEEK Compact PRO. However, the thermal images of FLIR One are noisier than SEEK Compact PRO since the thermal resolution of FLIR One is 160 × 120 while it is 320 × 240 in SEEK Compact PRO. CONCLUSION Detecting and revealing the inhomogeneous temperature distribution on the injured toe of the subject, we, in this paper, analyzed the imaging results of two different smartphone-based thermal camera models by making comparison among various thermograms. Utilizing the feasibility of the proposed method for faster and comparative diagnosis in biomedical problems is the main contribution of this study.
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Affiliation(s)
- Ayca Kirimtat
- Faculty of Informatics and Management, Center for Basic and Applied Research, University of Hradec Kralove, Rokitanskeho 62, 500 03 Hradec Kralove, Czech Republic
| | - Ondrej Krejcar
- Faculty of Informatics and Management, Center for Basic and Applied Research, University of Hradec Kralove, Rokitanskeho 62, 500 03 Hradec Kralove, Czech Republic
| | - Ali Selamat
- Faculty of Informatics and Management, Center for Basic and Applied Research, University of Hradec Kralove, Rokitanskeho 62, 500 03 Hradec Kralove, Czech Republic
- Malaysia Japan International Institute of Technology (MJIIT), Universiti Teknologi Malaysia Kuala Lumpur, Jalan Sultan Yahya Petra, Kuala Lumpur, 54100 Malaysia
- Digital Cities Research Institute, Multimedia University, Persiaran Multimedia, Cyberjaya, 63100 Malaysia
- Media and Games Center of Excellence (MagicX) Universiti Teknologi Malaysia & School of Computing, Faculty of Engineering, Universiti Teknologi Malaysia, Skudai, 81310 Johor Malaysia
| | - Enrique Herrera-Viedma
- Andalusian Research Institute in Data Science and Computational Intelligence, University of Granada, 18071 Granada, Spain
- Department of Electrical and Computer Engineering, Faculty of Engineering, King Abdulaziz University, Jeddah, Saudi Arabia
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