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.
|Title of host publication||Unknown Host Publication|
|Number of pages||6|
|Publication status||Published (in print/issue) - Oct 2003|
|Event||2003 IEEE Int. Conf. Systems Man and Cybernetics - Washington, DC, USA|
Duration: 1 Oct 2003 → …
|Conference||2003 IEEE Int. Conf. Systems Man and Cybernetics|
|Period||1/10/03 → …|