Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/25510
Title: A review on methods and software for fuzzy cognitive maps
Authors: Felix, Gerardo
NAPOLES RUIZ, Gonzalo 
Falcon, Rafael
Froelich, Wojciech
VANHOOF, Koen 
Bello, Rafael
Issue Date: 2017
Source: Artificial intelligence review, 52 (3), p. 1707-1737
Abstract: Fuzzy Cognitive Maps (FCMs) keep growing in popularity within the scientific community. However, despite substantial advances in the theory and applications of FCMs, there is a lack of an up-to-date, comprehensive presentation of the state-of-the-art in this domain. In this review study we are filling that gap. First, we present basic FCM concepts and analyze their static and dynamic properties, and next we elaborate on existing algorithms used for learning the FCM structure. Second, we provide a goal-driven overview of numerous theoretical developments recently reported in this area. Moreover, we consider the application of FCMs to time series forecasting and classification. Finally, in order to support the readers in their own research, we provide an overview of the existing software tools enabling the implementation of both existing FCM schemes as well as prospective theoretical and/or practical contributions.
Notes: Felix, G (reprint author), Cent Univ Las Villas, Santa Clara, Cuba. gerardfelix87@gmail.com; gonzalo.napoles@uhasselt.be; rfalcon@uottawa.ca; wojciech.froelich@us.edu.pl; koen.vanhoof@uhasselt.be; rbellop@uclv.cu
Keywords: Fuzzy Cognitive Maps; Machine Learning; Software Tools
Document URI: http://hdl.handle.net/1942/25510
ISSN: 0269-2821
e-ISSN: 1573-7462
DOI: 10.1007/s10462-017-9575-1
ISI #: 000486256400006
Rights: © Springer Science+Business Media B.V. 2017
Category: A1
Type: Journal Contribution
Validations: ecoom 2020
vabb 2019
Appears in Collections:Research publications

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