FCMpy: A Python Module for Constructing and Analyzing Fuzzy Cognitive Maps
FCMpy is an open source package in Python for building and analyzing Fuzzy Cognitive Maps. More specifically, the package allows 1) deriving fuzzy causal weights from qualitative data, 2) simulating the system behavior, 3) applying machine learning algorithms (e.g., Nonlinear Hebbian Learning, Activ...
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| Published in | arXiv.org |
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| Main Authors | , , , , , |
| Format | Paper Journal Article |
| Language | English |
| Published |
Ithaca
Cornell University Library, arXiv.org
24.11.2021
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| Online Access | Get full text |
| ISSN | 2331-8422 |
| DOI | 10.48550/arxiv.2111.12749 |
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| Abstract | FCMpy is an open source package in Python for building and analyzing Fuzzy Cognitive Maps. More specifically, the package allows 1) deriving fuzzy causal weights from qualitative data, 2) simulating the system behavior, 3) applying 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, and 4) implementing scenario analysis by simulating hypothetical interventions (i.e., analyzing what-if scenarios). |
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| AbstractList | FCMpy is an open source package in Python for building and analyzing Fuzzy Cognitive Maps. More specifically, the package allows 1) deriving fuzzy causal weights from qualitative data, 2) simulating the system behavior, 3) applying 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, and 4) implementing scenario analysis by simulating hypothetical interventions (i.e., analyzing what-if scenarios). PeerJ Computer Science 8:e1078, 2022 FCMpy is an open source package in Python for building and analyzing Fuzzy Cognitive Maps. More specifically, the package allows 1) deriving fuzzy causal weights from qualitative data, 2) simulating the system behavior, 3) applying 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, and 4) implementing scenario analysis by simulating hypothetical interventions (i.e., analyzing what-if scenarios). |
| Author | Giabbanelli, Philippe J Wozniak, Maciej K Crutzen, Rik de Vries, Nanne K Mkhitaryan, Samvel Napoles, Gonzalo |
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| BackLink | https://doi.org/10.7717/peerj-cs.1078$$DView published paper (Access to full text may be restricted) https://doi.org/10.48550/arXiv.2111.12749$$DView paper in arXiv |
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| DOI | 10.48550/arxiv.2111.12749 |
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| Snippet | FCMpy is an open source package in Python for building and analyzing Fuzzy Cognitive Maps. More specifically, the package allows 1) deriving fuzzy causal... PeerJ Computer Science 8:e1078, 2022 FCMpy is an open source package in Python for building and analyzing Fuzzy Cognitive Maps. More specifically, the package... |
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| SubjectTerms | Algorithms Cognitive maps Cognitive models Computer Science - Learning Computer Science - Mathematical Software Genetic algorithms Machine learning Qualitative analysis |
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| Title | FCMpy: A Python Module for Constructing and Analyzing Fuzzy Cognitive Maps |
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