THE PARAMETER OPTIMIZATION OF MMNN BASED ON GENETIC ALGORITHM COMBINED WITH SIMULATED ANNEALING AND ITS APPLICATION
Zhou Yue①; Xiang Jinglin②; Yang Jie①
①Inst. of Image Processing and Pattern Recognition Jiaotong Univ.,Shanghai 200030 China;②College of Marine Eng.,Northwestern Polytechnical Univ., Xi an 710072 China
Abstract:In this paper, the structure and algorithm of Max-Min fuzzy neural network (MMNN) are studied in detail. In order to get rid of some intrinsic localization of the method and boost up the capability of the MMNN, a series of steps are presented and the improved project (IMMNN) is gained. With a view to making the capability even much better and compressing the time of the convergence, the op-IMMNN is put forward in which the parameters of IMMNN are optimized by genetic algorithm combined with simulated annealing. In the simula-
tion, the result of op-IMMNN is superior over the conventional MMNN’s. Finally, a satisfactory result is also obtained when op-IMMNN is regarded as a classifier to distinguish the types of the ships according to their actual radiated noise. Comparing with the neural network based on the back propagation algorithm, the advantages of the op-IMMNN are fully put up.
周越; 相敬林; 杨杰. 基于模拟退火遗传算法的模糊分类器参数优化及其应用[J]. 电子与信息学报, 2001, 23(10): 975-983 .
Zhou Yue①; Xiang Jinglin②; Yang Jie①. THE PARAMETER OPTIMIZATION OF MMNN BASED ON GENETIC ALGORITHM COMBINED WITH SIMULATED ANNEALING AND ITS APPLICATION. , 2001, 23(10): 975-983 .