dc.contributor.authorHuang, Lei
dc.contributor.authorShi, Yikai
dc.contributor.authorYuan, Xiaoqing
dc.contributor.authorWang, Danwei
dc.contributor.authorYu, Ming
dc.date.accessioned2013-10-10T04:20:44Z
dc.date.available2013-10-10T04:20:44Z
dc.date.copyright2012en_US
dc.date.issued2012
dc.identifier.citationHuang, 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.
dc.identifier.urihttp://hdl.handle.net/10220/16369
dc.description.abstractA 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.en_US
dc.language.isoenen_US
dc.subjectDRNTU::Engineering::Electrical and electronic engineering
dc.titleWeight-varying neural network for parameter identification of automatic vehicleen_US
dc.typeConference Paper
dc.contributor.conferenceIEEE International Conference on Industrial Informatics (10th : 2012 : Beijing, China)en_US
dc.contributor.schoolSchool of Electrical and Electronic Engineeringen_US
dc.identifier.doihttp://dx.doi.org/10.1109/INDIN.2012.6301243


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