Title :
Hierarchical Modified RPSO based technique for optimal rule extraction
Author :
Mukhopadhyay, Sumitra ; Mandal, Ajit K.
Author_Institution :
Inst. of Radio Phys. & Electron., Univ. of Calcutta, Kolkata, India
Abstract :
In this paper, we present a Modified Robust Particle Swarm Optimization based learning technique for automatic extraction of fuzzy rules and subsequently for updating the parameters of a self-organized neuro-fuzzy network. The learning algorithm of network parameters is based on assigning balanced importance on local and global information. Experiments, conducted with standard benchmark problems, show the effectiveness of the method with a small number of rules along with comparable estimation error.
Keywords :
fuzzy set theory; network parameters; neural nets; particle swarm optimisation; comparable estimation error; fuzzy rules automatic extraction; global information; hierarchical modified RPSO based technique; modified robust particle swarm optimization; network parameters network algorithm; neurofuzzy network; optimal rule extraction; standard benchmark problems; Cognition; Data mining; Estimation error; Function approximation; Fuzzy logic; Fuzzy neural networks; Fuzzy systems; Neural networks; Particle swarm optimization; Robustness; Accommodation Boundary; Expert System; Modified RPSO; Robust Particle Swarm Optimization;
Conference_Titel :
Computers and Devices for Communication, 2009. CODEC 2009. 4th International Conference on
Conference_Location :
Kolkata
Print_ISBN :
978-1-4244-5073-2
