NDLI: A hierarchical genetic algorithm based RBF neural network approach for modelling of electrohydraulic system

Content Provider	IEEE Xplore Digital Library
Author	Xing Zong-yi Zhang Yuan Qin Yong Jia Li-min Wu Ying-ying
Copyright Year	2009
Description	Author affiliation: School of mechanical engineering, Nanjing University of Science and Technology, Jiangsu, China (Xing Zong-yi; Zhang Yuan; Wu Ying-ying) \|\| School of Traffic and Transportation, Beijing Jiaotong University, China (Qin Yong; Jia Li-min)
Abstract	The paper presents an approach to model the electrohydraulic system of a certain mine-sweeping weapon using the Radial Basis Function (RBF) neural networks. In order to obtain accurate and simple RBF neural networks efficiently, a hierarchical genetic algorithm (HGA) is used to train the neural networks, in which the number of hidden units and the parameters of centers are optimized by the HGA simultaneously. The spread factors and the weights of the neural networks are calculated by the linear algebra methods for relieving computational burden. The proposed algorithm is applied to the modelling of the electrohydraulic system, and the results clearly indicate that the obtained RBF neural network can model the hydraulic system satisfactorily. The comparison results also show that the proposed algorithm performs better than the traditional methods.
Starting Page	1018
Ending Page	1022
File Size	272358
Page Count	5
File Format	PDF
ISBN	9784907764340
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-08-18
Publisher Place	Japan
Access Restriction	Subscribed
Rights Holder	SICE
Subject Keyword	Genetic algorithms Neural networks Electrohydraulics Clustering algorithms Electronic mail Fluid flow control Educational institutions Mechanical engineering Paper technology Telecommunication traffic electrohydraulic system neural network hierarchical genetic algorithm modeling
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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