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Proceedings of 2009 International Workshop on Information Security and Application (IWISA 2009)

Qingdao, China, November 21-22, 2009

Editors: Feng Gao and Xijun Zhu

AP Catalog Number: AP-PROC-CS-09CN004

ISBN: 978-952-5726-06-0

Page(s): 664-668

A Misfire Diagnosis System for Automobile Engines Based on Genetic Algorithms and Fuzzy Neural Network

Di Lu and Yinhua Liu

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For common misfiring fault of automobile engines, this paper presents an algorithm named GA-FNN which is the combination of the genetic algorithm (GA) and the fuzzy neural network (FNN). It calculates the memberships of inputs and initializes the weights and thresholds of the neural network by genetic algorithm firstly, and then trains the network and uses it for diagnosis. Simulation results demonstrate GA-FNN has better precision and convergence than FNN. Lastly, GA-FNN is embedded into the expert system with an interactive interface for users.

Index Terms

misfire, diagnosis, genetic algorithm, fuzzy neural network, expert system

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