In spite of great importance of fuzzy feed-forward and recurrent neural networks (FNN) for solving wide range of real-world problems, today there is no e ective learning algorithm for FNN. In this paper we propose an e ective geneticbased learning mechanism for FNN with fuzzy inputs, fuzzy weights e
β¦ LIBER β¦
Learning feed-forward and recurrent fuzzy systems: A genetic approach
β Scribed by Hartmut Surmann; Michail Maniadakis
- Publisher
- Elsevier Science
- Year
- 2001
- Tongue
- English
- Weight
- 345 KB
- Volume
- 47
- Category
- Article
- ISSN
- 1383-7621
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main aim of this paper is to present MOGUL, a Methodology to Obtain Genetic fuzzy rule-based systems Under the iterative rule Learning approach. MOGUL will consist of some design guidelines that allow us to obtain different genetic fuzzy rule-based systems, i.e., evolutionary algorithm-based process