Modeling and Forecasting of Well-Being Using Fuzzy Cognitive Maps
In this paper we address the problem of modeling and forecasting of well-being. First, we apply a graph-based model of a Fuzzy cognitive map to discover cause-and-effect relationships among indicators of well-being. Second, the discovered model is applied to forecast the future state of well-being. The model is constructed using historical multivariate time series containing six consolidated indexes that represent well-being on the considered territory. Experiments with real-world data provided evidence for the usefulness of the proposed approach. Moreover, the interpretation of the obtained FCM graph led to the discovery of unknown dependencies within the data. The analysis of the unknown dependencies requires further research.
The reported study was funded by RFBR according to the research project No. 16-37-00014-mol_a.
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