Genetic Recurrent Fuzzy System by Coevolutionary Computation With Divide-and-Conquer Technique  

Oleh:

Juang, Chia-Feng

Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: IEEE Transactions on Systems, Man, and Cybernetics: Part C Applications and Reviews vol. 35 no. 2 (May 2005), page 249-254.
Topik: Dynamic Plant Control; Elite Strategy; Fuzzy Control; Premature Convergence; Recurrent Neural Network.

Ketersediaan

Perpustakaan Pusat (Semanggi) Nomor Panggil: II69.1 Non-tandon: 1 (dapat dipinjam: 0) Tandon: tidak ada

Lihat Detail Induk

Isi artikel

A genetic recurrent fuzzy system which automates the design of recurrent fuzzy networks by a coevolutionary genetic algorithm with divide-and-conquer technique (CGA-DC) is proposed in this paper. To solve temporal problems, the recurrent fuzzy network constructed from a series of recurrent fuzzy if-then rules is adopted. In the CGA-DC, based on the structure of a recurrent fuzzy network, the design problem is divided into the design of individual subrules, including spatial and temporal, and that of the whole network. Then, three populations are created, among which two are created for spatial and temporal subrules searches, and the other for the whole network search. Evolution of the three populations are performed independently and concurrently to achieve a good design performance. To demonstrate the performance of CGA-DC, temporal problems on dynamic plant control and chaotic system processing are simulated. In this way, the efficacy and efficiency of CGA-DC can be evaluated as compared with other genetic-algorithm-based design approaches.

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