Title :
The Neural-fuzzy Modeling and Genetic Optimization in WEDM
Author :
Guiqin, Li ; Fanhui, Kong ; Wenle, Lu ; Qingfeng, Yuan ; Minglun, Fang
Author_Institution :
Shanghai Univ., Shanghai
fDate :
May 30 2007-June 1 2007
Abstract :
Considering the needs for getting more precise parameters and at the same time to get faster cutting speed and better surface roughness in Wire Electrical Discharge Machining (WEDM), the authors established a model of WEDM, which has higher forecast precision and generalization ability and could help us in getting better understanding of the basic principles of WEDM. The model combined modeling function of fuzzy inference with the learning ability of artificial neural network; and a set of rules has been generated directly from the experimental data. Integrated with the genetic optimization procedure, the fuzzy inference systems are used to optimize the wire electrical discharge model of WEDM and the optimum results of the model have proved the feasibility and practicability of the system in WEDM.
Keywords :
electrical discharge machining; fuzzy neural nets; fuzzy reasoning; genetic algorithms; production engineering computing; artificial neural network; fuzzy inference systems; genetic optimization; modeling function; neural-fuzzy modeling; wire electrical discharge machining; Fuzzy neural networks; Fuzzy sets; Genetics; Load forecasting; Machining; Predictive models; Rough surfaces; Surface discharges; Surface roughness; Wire; Fuzzy Neural Network(FNN); Wire Electrical Discharge Machining(WEDM); fuzzy inference; genetic optimization;
Conference_Titel :
Control and Automation, 2007. ICCA 2007. IEEE International Conference on
Conference_Location :
Guangzhou
Print_ISBN :
978-1-4244-0818-4
Electronic_ISBN :
978-1-4244-0818-4
DOI :
10.1109/ICCA.2007.4376599
