期刊
PEERJ COMPUTER SCIENCE
卷 8, 期 -, 页码 -出版社
PEERJ INC
DOI: 10.7717/peerj-cs.1078
关键词
Active Hebbian learning; FCM; Genetic algorithm; Nonlinear Hebbian learning; Python
FCMpy is an open-source Python module that provides tools for building and analyzing Fuzzy Cognitive Maps (FCMs) in end-to-end projects. It allows users to derive fuzzy causal weights, implement machine learning algorithms, and conduct scenario analysis. The module aims to facilitate the development and testing of FCM models for researchers from various fields.
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.
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