A review on methods and software for fuzzy cognitive maps

Gerardo Felix; Gonzalo Nápoles; Rafael Falcon; Wojciech Froelich; Koen Vanhoof; Rafael Bello

doi:10.1007/s10462-017-9575-1

A review on methods and software for fuzzy cognitive maps

Gerardo Felix^*, Gonzalo Nápoles, Rafael Falcon, Wojciech Froelich, Koen Vanhoof, Rafael Bello

^*Corresponding author for this work

Research output: Contribution to journal › Article › Scientific › peer-review

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.

Original language	English
Pages (from-to)	1707-1737
Number of pages	31
Journal	Artificial Intelligence Review
Volume	52
Issue number	3
DOIs	https://doi.org/10.1007/s10462-017-9575-1
Publication status	Published - 2019
Externally published	Yes

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title = "A review on methods and software for fuzzy cognitive maps",

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.",

author = "Gerardo Felix and Gonzalo N{\'a}poles and Rafael Falcon and Wojciech Froelich and Koen Vanhoof and Rafael Bello",

year = "2019",

doi = "10.1007/s10462-017-9575-1",

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T1 - A review on methods and software for fuzzy cognitive maps

AU - Felix, Gerardo

AU - Nápoles, Gonzalo

AU - Falcon, Rafael

AU - Froelich, Wojciech

AU - Vanhoof, Koen

AU - Bello, Rafael

PY - 2019

Y1 - 2019

N2 - 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.

AB - 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.

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DO - 10.1007/s10462-017-9575-1

M3 - Article

VL - 52

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EP - 1737

JO - Artificial intelligence review: An international survey and tutorial journal

JF - Artificial intelligence review: An international survey and tutorial journal

SN - 0269-2821

IS - 3

ER -

A review on methods and software for fuzzy cognitive maps

Abstract

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