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Pang K, Liu P, Li S, Zou L, Lu M, Martínez L. Concept lattice simplification with fuzzy linguistic information based on three-way clustering. Int J Approx Reason 2023. [DOI: 10.1016/j.ijar.2022.12.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
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2
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Salimian S, Mousavi SM. A Multi-Criteria Decision-Making Model with Interval-Valued Intuitionistic Fuzzy Sets for Evaluating Digital Technology Strategies in COVID-19 Pandemic Under Uncertainty. ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING 2022; 48:7005-7017. [PMID: 36090763 PMCID: PMC9446620 DOI: 10.1007/s13369-022-07168-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/04/2021] [Accepted: 07/26/2022] [Indexed: 11/27/2022]
Abstract
Coronavirus diseases 2019 (COVID-19) pandemic is an essential challenge to the health and safety of people, medical members, and treatment systems worldwide. Digital technologies (DTs) have been universally introduced to improve the treatment of patients during the pandemic. Nevertheless, only a few governments have been partly successful in executing the DT strategies. In this regard, it is critical to demonstrate a suitable strategy for the governments. This problem is built based on the experts' opinions with some conflicting criteria to evaluate various types of alternatives. Hence, this research presents a new multi-criteria decision-making (MCDM) model under uncertain conditions. For this reason, interval-valued intuitionistic fuzzy sets (IVIFSs) are employed to help decision-makers (DMs) evaluate in a broader area and cope with uncertain information. Moreover, a new extended weighting method based on weighted distance-based approximation (WDBA) and a new combined ranking approach are proposed to determine the DMs' weights and rank the alternatives under IVIF conditions. The developed weighting method is constructed based on computing the DMs' weights with objective criteria weights. Furthermore, a new ranking approach is proposed by obtaining two ranking indexes separately: The first and second ranking indexes are calculated according to the positive and negative ideal solutions distances and the nature of criteria weights, respectively. Afterward, the final values of rankings are computed by considering a new aggregating procedure. The results of the proposed model represent the first alternative as the best strategy. Comparisons between the IVIF-TOPSIS and IVIF-VIKOR methods are also provided to investigate the proposed model to determine the rankings of main alternatives. Sensitivity analyses are conducted to check the reliability and the robustness of the model. For this purpose, criteria weights are analyzed to compute the dependencies' degree of the new extended weighting method. The dependencies of the ranking model are discussed on the criteria weights as well.
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Affiliation(s)
- Sina Salimian
- Department of Industrial Engineering, Shahed University, Tehran, Iran
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3
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Wang P. Construction of a Prediction Model for Distance Education Quality Assessment Based on Convolutional Neural Network. COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE 2022; 2022:8937314. [PMID: 36105638 PMCID: PMC9467773 DOI: 10.1155/2022/8937314] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/04/2022] [Revised: 08/02/2022] [Accepted: 08/06/2022] [Indexed: 11/17/2022]
Abstract
This paper introduces the principles and operation steps of convolution and pooling of convolutional neural networks in detail. In view of the shortcomings of fixed sampling points and single receptive field in traditional convolution and pooling forms, deformable convolution and deformable pooling are introduced to enhance the network's ability to adapt to image details and large displacement problems. The concepts of warp, loop optimization, and network stack are introduced. In order to improve the optimization performance of the algorithm, three subnetwork structures and stack models are designed, and various methods are used to improve the prediction accuracy of distance education quality assessment. In order to improve the accuracy and timeliness of education quality assessment, this paper proposes a distance education quality assessment model based on mining algorithms. The prediction index is selected by the improved BP neural network. It is required to establish the input layer node as the input vector based on the number of data sources since the input layer is used for data input. The neural network is trained with a quarter of the mining data, and the mining algorithm is further trained with network error trials. A fuzzy relationship matrix is created based on the assessment of teaching quality's hierarchical structure. This leads to the conclusion of the fuzzy thorough evaluation of the effectiveness of distant learning. Experiments show that the proposed model has an average accuracy of 96%, the average teaching quality modeling time is 25.44 ms, and the evaluation speed is fast.
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Affiliation(s)
- Peizhang Wang
- School of Management, Anhui Science and Technology University, Chuzhou, Anhui 233100, China
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4
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Distance education quality evaluation based on multigranularity probabilistic linguistic term sets and disappointment theory. Inf Sci (N Y) 2022. [DOI: 10.1016/j.ins.2022.05.034] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
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5
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Wang H, Zhang F. Modified WASPAS method based on the pythagorean fuzzy frank interaction aggregation operators and its application in cloud computing product selection. JOURNAL OF INTELLIGENT & FUZZY SYSTEMS 2022. [DOI: 10.3233/jifs-213152] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Frank operations are more robust and flexible than other algebraic operations, and interaction operational laws consider interrelationship between membership functions in Pythagorean fuzzy number. Combining the strengths of both, we define some Frank interaction operational laws of Pythagorean fuzzy numbers for the first time in this article. Based on this, the Pythagorean fuzzy Frank interaction weighted averaging and geometric operators are developed. Meanwhile, we discuss their basic properties and related special cases. Furthermore, a novel multiple attribute decision-making framework is established based on the modified WASPAS method in Pythagorean fuzzy environment. The proposed method is implemented in a real-case study of cloud computing product selection to test the proposed methodology’s plausibility. A sensitivity analysis is conducted to verify our method’s reliability, and the effectiveness and superiority are illustrated by comparative study.
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Affiliation(s)
- Haolun Wang
- Research Center of the Central China for Economic and Social Development, Nanchang, China
- School of Economics and Management, Nanchang University, Nanchang, China
| | - Faming Zhang
- School of Business, Guilin University of Electronic Technology, Guilin, China
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6
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Alsalem MA, Mohammed R, Albahri OS, Zaidan AA, Alamoodi AH, Dawood K, Alnoor A, Albahri AS, Zaidan BB, Aickelin U, Alsattar H, Alazab M, Jumaah F. Rise of multiattribute decision-making in combating COVID-19: A systematic review of the state-of-the-art literature. INT J INTELL SYST 2022; 37:3514-3624. [PMID: 38607836 PMCID: PMC8653072 DOI: 10.1002/int.22699] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2021] [Revised: 09/08/2021] [Accepted: 09/16/2021] [Indexed: 12/17/2022]
Abstract
Considering the coronavirus disease 2019 (COVID-19) pandemic, the government and health sectors are incapable of making fast and reliable decisions, particularly given the various effects of decisions on different contexts or countries across multiple sectors. Therefore, leaders often seek decision support approaches to assist them in such scenarios. The most common decision support approach used in this regard is multiattribute decision-making (MADM). MADM can assist in enforcing the most ideal decision in the best way possible when fed with the appropriate evaluation criteria and aspects. MADM also has been of great aid to practitioners during the COVID-19 pandemic. Moreover, MADM shows resilience in mitigating consequences in health sectors and other fields. Therefore, this study aims to analyse the rise of MADM techniques in combating COVID-19 by presenting a systematic literature review of the state-of-the-art COVID-19 applications. Articles on related topics were searched in four major databases, namely, Web of Science, IEEE Xplore, ScienceDirect, and Scopus, from the beginning of the pandemic in 2019 to April 2021. Articles were selected on the basis of the inclusion and exclusion criteria for the identified systematic review protocol, and a total of 51 articles were obtained after screening and filtering. All these articles were formed into a coherent taxonomy to describe the corresponding current standpoints in the literature. This taxonomy was drawn on the basis of four major categories, namely, medical (n = 30), social (n = 4), economic (n = 13) and technological (n = 4). Deep analysis for each category was performed in terms of several aspects, including issues and challenges encountered, contributions, data set, evaluation criteria, MADM techniques, evaluation and validation and bibliography analysis. This study emphasised the current standpoint and opportunities for MADM in the midst of the COVID-19 pandemic and promoted additional efforts towards understanding and providing new potential future directions to fulfil the needs of this study field.
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Affiliation(s)
- Mohammed Assim Alsalem
- Department of Computing, Faculty of Arts, Computing and Creative IndustryUniversiti Pendidikan Sultan IdrisTanjung MalimMalaysia
| | - Rawia Mohammed
- Faculty of Computing and Innovative TechnologyGeomatika University CollegeKuala LumpurMalaysia
| | - Osamah Shihab Albahri
- Department of Computing, Faculty of Arts, Computing and Creative IndustryUniversiti Pendidikan Sultan IdrisTanjung MalimMalaysia
| | - Aws Alaa Zaidan
- Department of Computing, Faculty of Arts, Computing and Creative IndustryUniversiti Pendidikan Sultan IdrisTanjung MalimMalaysia
| | - Abdullah Hussein Alamoodi
- Department of Computing, Faculty of Arts, Computing and Creative IndustryUniversiti Pendidikan Sultan IdrisTanjung MalimMalaysia
| | - Kareem Dawood
- Computer Science DepartmentKomar University of Science and Technology (KUST)SulaymaniyahIraq
| | - Alhamzah Alnoor
- School of ManagementUniversiti Sains MalaysiaPulau PinangMalaysia
| | - Ahmed Shihab Albahri
- Informatics Institute for Postgraduate Studies (IIPS)Iraqi Commission for Computers and Informatics (ICCI)BaghdadIraq
| | - Bilal Bahaa Zaidan
- Future Technology Research CenterNational Yunlin University of Science and TechnologyDouliouTaiwan R.O.C.
| | - Uwe Aickelin
- School of Computing and Information SystemsThe University of MelbourneAustralia
| | - Hassan Alsattar
- Department of Computing, Faculty of Arts, Computing and Creative IndustryUniversiti Pendidikan Sultan IdrisTanjung MalimMalaysia
| | - Mamoun Alazab
- College of Engineering, IT and EnvironmentCharles Darwin UniversityCasuarinaNorthern TerritoryAustralia
| | - Fawaz Jumaah
- Department of Advanced Applications and Embedded SystemsIntel CorporationPulau PinangMalaysia
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7
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Issues and analysis of critical success factors for the sustainable initiatives in the supply chain during COVID- 19 pandemic outbreak in India: A case study. RESEARCH IN TRANSPORTATION ECONOMICS 2022; 93:101114. [PMCID: PMC9197267 DOI: 10.1016/j.retrec.2021.101114] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/31/2020] [Revised: 06/26/2021] [Accepted: 07/09/2021] [Indexed: 01/30/2024]
Abstract
The coronavirus (COVID-19) pandemic has severely affected the supply chain all over. A major challenge for the supply chain (SC) is to address this disruption risk and bring sustainability to SC. The objective of this paper is to identify the stakeholders' requirements and critical success factors (CSFs) for the sustainability initiative in SC during this pandemic situation. Three potential stakeholders' requirements and a total of 16 critical success factors have been identified by taking inputs from experts and decision-makers. Further, these critical factors are analyzed and ranked based on a hybrid quality function deployment (QFD)-best-worst methodology (BWM). The QFD method has been used to identify the stakeholder’ requirements. And, the BWM has been adopted to prioritize the CSFs. The scientific value of the study is the contribution of the framework model for the sustainable initiatives in the SC during the COVID-19 pandemic outbreak, identification of stakeholders’ requirements and CSFs, and prioritizes these CSFs. The top three most critical success factors are found to be social distancing, emergency logistics systems, and emergency backup facilities. The proposed framework provides a roadmap to operation and supply chain managers to come up with good solutions for sustainability initiatives in the supply chain during and after the pandemic outbreak.
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Waste Clothing Recycling Channel Selection Using a CoCoSo-D Method Based on Sine Trigonometric Interaction Operational Laws with Pythagorean Fuzzy Information. ENERGIES 2022. [DOI: 10.3390/en15062010] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Under the influence of circular economy theory, waste clothing recycling has been widely studied in the resource sector, and the waste clothing recycling channel (WCRC) is the vital link that affects the recycling efficiency of waste clothing. How to select the optimal WCRC is considered a typical multiple attribute group decision-making (MAGDM) problem. In this article, we develop sine trigonometric interaction operational laws (IOLs) (STIOLs) using Pythagorean fuzzy information. The sine trigonometric interaction Pythagorean fuzzy weighted averaging (STI-PyFWA) and sine trigonometric interaction Pythagorean fuzzy weighted geometric (STI-PyFWG) operators are advanced, and their several desirable properties are discussed. Further, we build a MAGDM framework based on the modified Pythagorean fuzzy CoCoSo (Combined Compromise Solution) method to solve the WCRC selection problem. The combined weight of attributes is determined, and the proposed aggregation operators (AOs) are applied to the CoCoSo method. A Pythagorean fuzzy distance measure is used to achieve the defuzzification of aggregation strategies. Finally, we deal with the WCRC selection problem for a sustainable environment by implementing the proposed method and performing sensitivity analysis and comparative study to validate its effectiveness and superiority.
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9
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Decision-making models based on satisfaction degree with incomplete hesitant fuzzy preference relation. Soft comput 2022. [DOI: 10.1007/s00500-021-06635-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
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10
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Alsalem MA, Alamoodi AH, Albahri OS, Dawood KA, Mohammed RT, Alnoor A, Zaidan AA, Albahri AS, Zaidan BB, Jumaah FM, Al-Obaidi JR. Multi-criteria decision-making for coronavirus disease 2019 applications: a theoretical analysis review. Artif Intell Rev 2022; 55:4979-5062. [PMID: 35103030 PMCID: PMC8791811 DOI: 10.1007/s10462-021-10124-x] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
The influence of the ongoing COVID-19 pandemic that is being felt in all spheres of our lives and has a remarkable effect on global health care delivery occurs amongst the ongoing global health crisis of patients and the required services. From the time of the first detection of infection amongst the public, researchers investigated various applications in the fight against the COVID-19 outbreak and outlined the crucial roles of different research areas in this unprecedented battle. In the context of existing studies in the literature surrounding COVID-19, related to medical treatment decisions, the dimensions of context addressed in previous multidisciplinary studies reveal the lack of appropriate decision mechanisms during the COVID-19 outbreak. Multiple criteria decision making (MCDM) has been applied widely in our daily lives in various ways with numerous successful stories to help analyse complex decisions and provide an accurate decision process. The rise of MCDM in combating COVID-19 from a theoretical perspective view needs further investigation to meet the important characteristic points that match integrating MCDM and COVID-19. To this end, a comprehensive review and an analysis of these multidisciplinary fields, carried out by different MCDM theories concerning COVID19 in complex case studies, are provided. Research directions on exploring the potentials of MCDM and enhancing its capabilities and power through two directions (i.e. development and evaluation) in COVID-19 are thoroughly discussed. In addition, Bibliometrics has been analysed, visualization and interpretation based on the evaluation and development category using R-tool involves; annual scientific production, country scientific production, Wordcloud, factor analysis in bibliographic, and country collaboration map. Furthermore, 8 characteristic points that go through the analysis based on new tables of information are highlighted and discussed to cover several important facts and percentages associated with standardising the evaluation criteria, MCDM theory in ranking alternatives and weighting criteria, operators used with the MCDM methods, normalisation types for the data used, MCDM theory contexts, selected experts ways, validation scheme for effective MCDM theory and the challenges of MCDM theory used in COVID-19 studies. Accordingly, a recommended MCDM theory solution is presented through three distinct phases as a future direction in COVID19 studies. Key phases of this methodology include the Fuzzy Delphi method for unifying criteria and establishing importance level, Fuzzy weighted Zero Inconsistency for weighting to mitigate the shortcomings of the previous weighting techniques and the MCDM approach by the name Fuzzy Decision by Opinion Score method for prioritising alternatives and providing a unique ranking solution. This study will provide MCDM researchers and the wider community an overview of the current status of MCDM evaluation and development methods and motivate researchers in harnessing MCDM potentials in tackling an accurate decision for different fields against COVID-19.
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Affiliation(s)
- M. A. Alsalem
- Department of Computing, Faculty of Arts, Computing and Creative Industry (FSKIK), Universiti Pendidikan Sultan Idris, Tanjung Malim, Malaysia
| | - A. H. Alamoodi
- Department of Computing, Faculty of Arts, Computing and Creative Industry (FSKIK), Universiti Pendidikan Sultan Idris, Tanjung Malim, Malaysia
| | - O. S. Albahri
- Department of Computing, Faculty of Arts, Computing and Creative Industry (FSKIK), Universiti Pendidikan Sultan Idris, Tanjung Malim, Malaysia
| | - K. A. Dawood
- Department of Computing Science, Komar University of Science and Technology (KUST), Sulaymaniyah, Iraq
| | - R. T. Mohammed
- Department of Computing Science, Komar University of Science and Technology (KUST), Sulaymaniyah, Iraq
| | - Alhamzah Alnoor
- School of Management, Universiti Sains Malaysia, Pulau Pinang, Malaysia
| | - A. A. Zaidan
- Faculty of Engineering & IT, British, University in Dubia, Dubai, United Arab Emirates
| | - A. S. Albahri
- Informatics Institute for Postgraduate Studies (IIPS), Iraqi Commission for Computers and Informatics (ICCI), Baghdad, Iraq
| | - B. B. Zaidan
- Future Technology Research Center, National Yunlin University of Science and Technology, 123 University Road, Section 3, 64002 Douliou, Yunlin Taiwan
| | - F. M. Jumaah
- Department of Advanced Applications and Embedded Systems, Intel Corporation, Plot 6, Bayan Lepas Technoplex, 11900 Pulau Pinang, Malaysia
- Computer Engineering and Software Engineering Department, Polytechnique Montréal, Montréal, Canada
| | - Jameel R. Al-Obaidi
- Department of Biology, Faculty of Science and Mathematics, Universiti Pendidikan Sultan Idris, 35900 Perak, Tanjong Malim Malaysia
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11
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Atıcı U, Adem A, Şenol MB, Dağdeviren M. A comprehensive decision framework with interval valued type-2 fuzzy AHP for evaluating all critical success factors of e-learning platforms. EDUCATION AND INFORMATION TECHNOLOGIES 2022; 27:5989-6014. [PMID: 35095324 PMCID: PMC8784212 DOI: 10.1007/s10639-021-10834-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/09/2021] [Accepted: 11/23/2021] [Indexed: 06/01/2023]
Abstract
The COVID 19 pandemic not only affected our health and social life in many aspects, but it also changed the classical way of training in classrooms and education preferences of society. As a solution various e-learning platforms were developed and preferred by many educational institutions where the individuals had the opportunity to try the advantages of e-learning platforms. Since the COVID-19 pandemic is neither the first nor the last epidemic, e-learning attracts more attention than ever before and the need for e-learning platforms is expected to be more in the near future. Thus it is necessary to define all critical success factors determining the efficiency of e-learning systems. E-learning platforms have advantages as well as disadvantages and comparisons involve uncertainties and qualitative assessments. A systematic approach should be used to determine the platforms' dimensions, features and weights of critical criteria. The motivation of our study is to determine the weights of all critical success criteria and offer a reliable method for evaluating e-learning platforms. In this study, the interval type-2 fuzzy Analytical Hierarchy Process was utilized to compare critical success factors of e-learning platforms. This is the most comprehensive study considering all critical success factors of e-learning platforms as an Multi Criteria decision Making problem, where 11 criteria and 106 sub-criteria were defined, evaluated and prioritized. This study provides an acceptable rationale for evaluations of e-learning platforms and the results of this study can be used in real-world performance evaluations.
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Affiliation(s)
- Uğur Atıcı
- Department of Industrial Engineering, Sivas Cumhuriyet University, Sivas, Türkiye
| | - Aylin Adem
- Department of Industrial Engineering, Gazi University, Ankara, Türkiye
| | | | - Metin Dağdeviren
- Department of Industrial Engineering, Gazi University, Ankara, Türkiye
- Council of Higher Education, Universiteler Mah. No:10, 06539 Bilkent-Ankara, Türkiye
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12
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Adem A, Çakıt E, Dağdeviren M. Selection of suitable distance education platforms based on human-computer interaction criteria under fuzzy environment. Neural Comput Appl 2022; 34:7919-7931. [PMID: 35068704 PMCID: PMC8762634 DOI: 10.1007/s00521-022-06935-w] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2021] [Accepted: 01/04/2022] [Indexed: 11/12/2022]
Abstract
The rapid spread of the COVID-19 pandemic has affected not only the health industry but also the education sector. E-learning systems have recently become a compulsory part of all education institutions, including schools, colleges, and universities worldwide because of the COVID-19 pandemic crisis. The objectives of the current study were twofold: (1) to conduct an analytical approach for ranking of distance education platforms based on human-computer interaction criteria and (2) to identify the most appropriate distance learning platform for teaching and learning activities by using multi-criteria decision-making approaches. Selection criteria were grouped into human-computer interaction-related criteria, such as ease of use, possibility of causing mental workload, user-friendly interface design, presentation method, and interactivity. In the selection procedure, a spherical fuzzy extension of Analytical Hierarchy Process was utilized to identify the weights of selection criteria and to rank distance education platforms. The results revealed that the most important criterion was the possibility of causing mental workload while the most preferable e-learning system was identified as "A3".
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Affiliation(s)
- Aylin Adem
- Department of Industrial Engineering, Gazi University, 06570 Ankara, Turkey
| | - Erman Çakıt
- Department of Industrial Engineering, Gazi University, 06570 Ankara, Turkey
| | - Metin Dağdeviren
- Department of Industrial Engineering, Gazi University, 06570 Ankara, Turkey
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13
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Interval type-2 hesitant fuzzy Entropy-based WASPAS approach for aircraft type selection. Appl Soft Comput 2022. [DOI: 10.1016/j.asoc.2021.108076] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
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14
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E-Learning Platform Assessment and Selection Using Two-Stage Multi-Criteria Decision-Making Approach with Grey Theory: A Case Study in Vietnam. MATHEMATICS 2021. [DOI: 10.3390/math9233136] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Education has changed dramatically due to the severe global pandemic COVID-19, with the phenomenal growth of e-learning, whereby teaching is undertaken remotely and on digital platforms. E-learning is revolutionizing education systems, as it remains the only option during the ongoing crisis and has tremendous potential to fulfill instructional plans and safeguard students’ learning rights. The selection of e-learning platforms is a multi-criteria decision-making (MCDM) problem. Expert analyses over numerous criteria and alternatives are usually linguistic terms, which can be represented through grey numbers. This article proposes an integrated approach of grey analytic hierarchy process (G-AHP) and grey technique for order preference by similarity to ideal solution (G-TOPSIS) to evaluate the best e-learning website for network teaching. This introduced approach handles the linguistic evaluation of experts based on grey systems theory, estimates the relative importance of evaluation criteria with the G-AHP method, and acquires e-learning websites’ ranking utilizing G-TOPSIS. The applicability and superiority of the presented method are illustrated through a practical e-learning website selection case in Vietnam. From G-AHP analysis, educational level, price, right and understandable content, complete content, and up-to-date were found as the most impactful criteria. From G-TOPSIS, Edumall is the best platform. Comparisons are conducted with other MCDM methods; the priority orders of the best websites are similar, indicating the robust proposed methodology. The proposed integrated model in this study supports the stakeholders in selecting the most effective e-learning environments and could be a reference for further development of e-learning teaching-learning systems.
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15
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New method for dependence assessment in human reliability analysis based on linguistic hesitant fuzzy information. NUCLEAR ENGINEERING AND TECHNOLOGY 2021. [DOI: 10.1016/j.net.2021.05.012] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
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16
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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] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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17
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Liu R, Zhu Y, Chen Y, Liu H. Occupational health and safety risk assessment using an integrated TODIM‐PROMETHEE model under linguistic spherical fuzzy environment. INT J INTELL SYST 2021. [DOI: 10.1002/int.22570] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Affiliation(s)
- Ran Liu
- School of Management Shanghai University Shanghai China
| | - Yu‐Jie Zhu
- School of Management Shanghai University Shanghai China
| | - Yao Chen
- Shanghai No. 3 Rehabilitation Hospital Shanghai China
| | - Hu‐Chen Liu
- College of Economics and Management China Jiliang University Hangzhou China
- School of Economics and Management Tongji University Shanghai China
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