Leng, G, McGinnity, TM and Prasad, G (2003) A Design for a Self-Organising Fuzzy Neural Network Based on the Genetic Algortihm. In: 2003 IEEE Int. Conf. Systems Man and Cybernetics, Washington, DC, USA. UNSPECIFIED. 6 pp. [Conference contribution]
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A novel hybrid algorithm based on the genetic algorithm, named self-organizing fuzzy neural network based on genetic algorithm (SOFNNGA), is proposed to design a fuzzy neural network to implement Takagi- Sugeno (TS) type fuzzy models in this paper. A new adding method based on geometric growing criterion and the å-completeness of fuzzy rules is used to generate the initial structure firstly. Then a hybrid algorithm based on genetic algorithms, backpropagation, and recursive least squares estimation is used to adjust all parameters, which has two steps: first, adjusting the parameter matrix, and second, centers and widths of all membership functions are modified. A simulation for a benchmark problem is presented to illustrate the performance of the proposed algorithm.
|Item Type:||Conference contribution (Paper)|
|Faculties and Schools:||Faculty of Computing & Engineering|
Faculty of Computing & Engineering > School of Computing and Intelligent Systems
|Research Institutes and Groups:||Computer Science Research Institute|
Computer Science Research Institute > Intelligent Systems Research Centre
|Deposited By:||Professor Martin McGinnity|
|Deposited On:||29 Jan 2010 15:26|
|Last Modified:||02 Feb 2012 15:15|
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