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FCMpy: a python module for constructing and analyzing fuzzy cognitive maps

delete2022-09-23
delete10
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OA
AI
S
Samvel Mkhitaryan *
P
Philippe J. Giabbanelli
M
Maciej K. Wozniak
G
Gonzalo Nápoles
N
Nanné K. de Vries
R
Rik Crutzen
DOI:10.7717/peerj-cs.1078delete
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Abstract

Abstract

En 中文
FCMpy is an open-source Python module for building and analyzing Fuzzy Cognitive Maps (FCMs). The module provides tools for end-to-end projects involving FCMs. It is able to derive fuzzy causal weights from qualitative data or simulating the system behavior. Additionally, it includes machine learning algorithms (e.g., Nonlinear Hebbian Learning, Active Hebbian Learning, Genetic Algorithms, and Deterministic Learning) to adjust the FCM causal weight matrix and to solve classification problems. Finally, users can easily implement scenario analysis by simulating hypothetical interventions (i.e., analyzing what-if scenarios). FCMpy is the first open-source module that contains all the functionalities necessary for FCM oriented projects. This work aims to enable researchers from different areas, such as psychology, cognitive science, or engineering, to easily and efficiently develop and test their FCM models without the need for extensive programming knowledge.
Keywords:
Active Hebbian learning
FCM
Genetic algorithm
Nonlinear Hebbian learning
Python
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PeerJ Computer Science cover
PeerJ Computer Science
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