Title :
Application of genetic algorithms to the structure optimization of radial basis probabilistic neural networks
Author :
Zhao, Wenbo ; Huang, De-Shuang ; Yunjian, Ge
Author_Institution :
Dept. of Autom., Univ. of Sci. & Technol. of China, China
Abstract :
The genetic algorithm (GA) is applied in this paper to select hidden centers of radial basis probabilistic neural networks (RBPNN). The encoding method of individuals for GA, proposed in this paper, embodies not only the number but also the positions of selected centers. In addition, precision control is integrated into definition of the fitness function. Finally, we use the two-dimensional Gaussian distribution classification problem to illustrate the performance of the GA.
Keywords :
Gaussian distribution; genetic algorithms; radial basis function networks; signal classification; RBPNN; encoding method; fitness function; genetic algorithms; precision control; radial basis probabilistic neural networks; structure optimization; two-dimensional Gaussian distribution classification; Algorithm design and analysis; Computational modeling; Encoding; Gaussian distribution; Genetic algorithms; Machine intelligence; Mathematics; Neural networks; Radial basis function networks; Terminology;
Conference_Titel :
Signal Processing, 2002 6th International Conference on
Print_ISBN :
0-7803-7488-6
DOI :
10.1109/ICOSP.2002.1180016
