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Vehicle simulation and test system based on RBFNN and its improved algorithm

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

According to the characteristics of the vehicle simulation and test system, we set up the vehicle acceleration and engine speed model, and RBF neural network is applied in this model. Since ordinary RBF network has poor adaptability, NRBF and Classified-RBF is proposed in this paper. The simulation results show that both methods can fit the model well, and the output error actually decreases to about half. The adaptability of the RBF network is improved. These can be used in the data fusion of the vehicle simulation and test system.

Original languageEnglish
Title of host publicationProceedings - 2012 International Conference on Computer Science and Information Processing, CSIP 2012
Pages790-794
Number of pages5
DOIs
StatePublished - 2012
Event2012 International Conference on Computer Science and Information Processing, CSIP 2012 - Xi'an, Shaanxi, China
Duration: 24 Aug 201226 Aug 2012

Publication series

NameProceedings - 2012 International Conference on Computer Science and Information Processing, CSIP 2012

Conference

Conference2012 International Conference on Computer Science and Information Processing, CSIP 2012
Country/TerritoryChina
CityXi'an, Shaanxi
Period24/08/1226/08/12

Keywords

  • NRBF
  • RBF neural network
  • simulation
  • vehicle test system

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