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For: Fazel Zarandi M, Soltanzadeh S, Mohammadi A, Castillo O. Designing a general type-2 fuzzy expert system for diagnosis of depression. Appl Soft Comput 2019;80:329-41. [DOI: 10.1016/j.asoc.2019.03.027] [Citation(s) in RCA: 36] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Number Cited by Other Article(s)
1
Nowakowska K, Sakellarios A, Kaźmierski J, Fotiadis DI, Pezoulas VC. AI-Enhanced Predictive Modeling for Identifying Depression and Delirium in Cardiovascular Patients Scheduled for Cardiac Surgery. Diagnostics (Basel) 2023;14:67. [PMID: 38201376 PMCID: PMC10795764 DOI: 10.3390/diagnostics14010067] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2023] [Revised: 12/21/2023] [Accepted: 12/26/2023] [Indexed: 01/12/2024]  Open
2
Using type-2 fuzzy ontology to improve semantic interoperability for healthcare and diagnosis of depression. Artif Intell Med 2023;135:102452. [PMID: 36628789 DOI: 10.1016/j.artmed.2022.102452] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2022] [Revised: 10/08/2022] [Accepted: 11/11/2022] [Indexed: 11/19/2022]
3
Malhotra A, Jindal R. Deep learning techniques for suicide and depression detection from online social media: A scoping review. Appl Soft Comput 2022. [DOI: 10.1016/j.asoc.2022.109713] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
4
Literature review on type-2 fuzzy set theory. Soft comput 2022. [DOI: 10.1007/s00500-022-07304-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/15/2022]
5
Efficient Algorithms for Data Processing under Type-3 (and Higher) Fuzzy Uncertainty. MATHEMATICS 2022. [DOI: 10.3390/math10132361] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
6
Barcellos‐Paula L, La Vega I, Gil‐Lafuente AM. Bibliometric review of research on decision models in uncertainty, 1990–2020. INT J INTELL SYST 2022. [DOI: 10.1002/int.22882] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
7
Matinfar F, Tavakoli Golpaygani A. A Fuzzy Expert System for Early Diagnosis of Multiple Sclerosis. J Biomed Phys Eng 2022;12:181-188. [PMID: 35433516 PMCID: PMC8995753 DOI: 10.31661/jbpe.v0i0.1236] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2019] [Accepted: 09/22/2019] [Indexed: 06/06/2023]
8
Interval type-2 fuzzy neural network based constrained GPC for NH$$_{3}$$ flow in SCR de-NO$$_{x}$$ process. Neural Comput Appl 2021. [DOI: 10.1007/s00521-021-06227-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
9
Zulfiker MS, Kabir N, Biswas AA, Nazneen T, Uddin MS. An in-depth analysis of machine learning approaches to predict depression. CURRENT RESEARCH IN BEHAVIORAL SCIENCES 2021. [DOI: 10.1016/j.crbeha.2021.100044] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]  Open
10
Qasem SN, Ahmadian A, Mohammadzadeh A, Rathinasamy S, Pahlevanzadeh B. A type-3 logic fuzzy system: Optimized by a correntropy based Kalman filter with adaptive fuzzy kernel size. Inf Sci (N Y) 2021. [DOI: 10.1016/j.ins.2021.05.031] [Citation(s) in RCA: 32] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
11
Observer-based interval type-2 fuzzy friction modeling and compensation control for steer-by-wire system. Neural Comput Appl 2021. [DOI: 10.1007/s00521-021-05801-5] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
12
Das S, Garg A, Maiti J, Krishna O, Thakkar JJ, Gangwar R. A comprehensive methodology for quantification of Bow-tie under type II fuzzy data. Appl Soft Comput 2021. [DOI: 10.1016/j.asoc.2021.107148] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
13
Wang J, Li H, Yang H, Wang Y. Intelligent multivariable air-quality forecasting system based on feature selection and modified evolving interval type-2 quantum fuzzy neural network. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2021;274:116429. [PMID: 33545527 DOI: 10.1016/j.envpol.2021.116429] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/04/2020] [Revised: 12/26/2020] [Accepted: 01/02/2021] [Indexed: 06/12/2023]
14
A new adaptive non-singleton general type-2 fuzzy control of induction motors subject to unknown time-varying dynamics and unknown load torque. Soft comput 2021. [DOI: 10.1007/s00500-021-05582-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
15
A review on type-2 fuzzy neural networks for system identification. Soft comput 2021;25:7197-7212. [PMID: 33716561 PMCID: PMC7941344 DOI: 10.1007/s00500-021-05686-5] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/10/2021] [Indexed: 12/05/2022]
16
Gribova V, Shalfeeva E. Ontology of anomalous processes diagnosis. INT J INTELL SYST 2021. [DOI: 10.1002/int.22300] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
17
Ontiveros-Robles E, Castillo O, Melin P. An approach for non-singleton generalized Type-2 fuzzy classifiers. JOURNAL OF INTELLIGENT & FUZZY SYSTEMS 2020. [DOI: 10.3233/jifs-200639] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
18
Type-2 fuzzy multigranulation rough sets. Int J Approx Reason 2020. [DOI: 10.1016/j.ijar.2020.06.007] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
19
Li P, Shen Y. Adaptive Sampled-Data Observer Design for a Class of Nonlinear Systems with Unknown Hysteresis. Neural Process Lett 2020. [DOI: 10.1007/s11063-020-10275-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
20
Uriz M, Elkano M, Bustince H, Galar M. FUZZ-EQ: A data equalizer for boosting the discrimination power of fuzzy classifiers. Appl Soft Comput 2020. [DOI: 10.1016/j.asoc.2020.106399] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
21
Rezaei Kalantari K, Ebrahimnejad A, Motameni H. Presenting a new fuzzy system for web service selection aimed at dynamic software rejuvenation. COMPLEX INTELL SYST 2020. [DOI: 10.1007/s40747-020-00168-x] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
22
Type II fuzzy set-based data analytics to explore amino acid associations in protein sequences of Swine Influenza Virus. Appl Soft Comput 2020. [DOI: 10.1016/j.asoc.2019.105856] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
23
Dynamic adaptation of the PID’s gains via Interval type-1 non-singleton type-2 fuzzy logic systems whose parameters are adapted using the backpropagation learning algorithm. Soft comput 2020. [DOI: 10.1007/s00500-019-04360-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
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