Continuous genetic algorithm-based fuzzy neural network for learning fuzzy IF-THEN rules
نویسندگان
چکیده
This study proposes a fuzzy neural network (FNN) that can process both fuzzy inputs and outputs. The continuous genetic algorithm (CGA) is employed to enhance its performance. Both the simulation and real-world problem results show that the proposed CGA-based FNN can obtain the relationship between fuzzy inputs and outputs. CGA can not only shorten the training time but also increase the accuracy for the FNN.
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ورودعنوان ژورنال:
- Neurocomputing
دوره 71 شماره
صفحات -
تاریخ انتشار 2008