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- W2891842289 abstract "Fuzzy cognitive map (FCM) allows to discover knowledge in the form of concepts significant for the analyzed problem and causal connections between them. The FCM model can be developed by experts or using learning algorithms and available data. The main aspect of building of the FCM model is concepts selection. It is usually based on the expert knowledge. The aim of this paper is to present the developed evolutionary algorithm for structure optimization and learning of fuzzy cognitive map on the basis of available data. The proposed approach allows to select key concepts during learning process based on metrics from the area of graph theory: significance of each node, total value of a node and total influence of the concept and determine the weights of the connections between them. A simulation analysis of the developed algorithm was done with the use of synthetic and real-life data." @default.
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- W2891842289 date "2018-09-19" @default.
- W2891842289 modified "2023-09-25" @default.
- W2891842289 title "Structure Optimization and Learning of Fuzzy Cognitive Map with the Use of Evolutionary Algorithm and Graph Theory Metrics" @default.
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- W2891842289 doi "https://doi.org/10.1007/978-3-319-99648-6_8" @default.
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