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Title: Weight-varying neural network for parameter identification of automatic vehicle
Authors: Huang, Lei
Shi, Yikai
Yuan, Xiaoqing
Wang, Danwei
Yu, Ming
Keywords: DRNTU::Engineering::Electrical and electronic engineering
Issue Date: 2012
Source: Huang, L., Shi, Y., Yuan, X., Wang, D., & Yu, M. (2012). Weight-varying neural network for parameter identification of automatic vehicle. 2012 10th IEEE International Conference on Industrial Informatics (INDIN), pp.766-771.
Abstract: A Bond Graph model is built for the steering system of automatic vehicle and a set of model equations are derived for further analysis purpose. For identifying several uncertain parameters, an integrative approach that combine least square method with Bp Neural Network algorithm (NN) is proposed, based on features of NN algorithm, two key improvements are bring into the training method of Bp NN: taking the identification result of least square method as initial weight value of network training, and introducing weight factor to improve the convergence property of Bp NN. The effectiveness of proposed approach is verified through experiment, and the result indicates that the reformatory Bp NN algorithm has higher identification accuracy.
DOI: 10.1109/INDIN.2012.6301243
Fulltext Permission: none
Fulltext Availability: No Fulltext
Appears in Collections:EEE Conference Papers

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