A curious learning model with ELM for fuzzy cognitive maps. (English) Zbl 1322.68150
Summary: The design of fuzzy cognitive maps (FCMs) mainly relies on human knowledge, which implies subjectivity of the developed model. This affects the accuracy of an FCM significantly. In order to address this issue, we propose a novel learning model for FCMs in this paper. It achieves efficient learning by automatically adjusting the system parameters according to the environment. The learning model consists of extreme learning machine (ELM) and a curious model, where ELM learns from the modeled system and the curious model helps to further improve the performance of ELM. We use an example to illustrate the effectiveness of our model. The simulation results show that our model helps to improve the accuracy of FCMs.
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