A Hierarchical Recurrent Neuro-Fuzzy System
نویسنده
چکیده
Fuzzy systems, neural networks and its combination in neuro-fuzzy systems are already well established in data analysis and system control. Especially, neurofuzzy systems are well suited for the development of interactive data analysis tools, which enable the creation of rule-based knowledge from data and the introduction of a-priori knowledge into the process of data analysis. However, its recurrent variants especially recurrent neuro-fuzzy models are still rarely used. In this article a (hybrid) recurrent neuro-fuzzy model is presented which is designed for application in time series prediction and identification of dynamic systems. It has been implemented in a tool for the interactive design of hierarchical recurrent fuzzy systems.
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