| Research on Tire Rolling Resistance Modeling Based on RBF Neural Network |
| Received:July 20, 2019 Revised:July 20, 2019 |
| DOI：10.12136/j.issn.1000-890X.2019.10.0739 |
| Key Words: tire；rolling resistance；model；RBF；BP；neural network |
| Author Name | Affiliation | E-mail | | MAO Xinxin* | Dalian Maritime University | mxx0105@126.com | | MAO Jianqing | Zhongce Rubber Co. ，Ltd | | | WANG Dongzhe | Dalian Maritime University | |
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| Abstract: |
| A tire rolling resistance model based on radial basis function （RBF）neural network was established，taking full use of the advantages of RBF network model，such as high approximation accuracy，
fast training speed and no local minimum，to predict tire rolling resistance comprehensively and accurately.
The results showed that the average relative errors of the prediction values of tire rolling resistance RBF
neural network model and back propagation（BP）neural network model were about 2% and 6%，respectively.
RBF neural network model showed advantages in training and prediction results，and could effectively predict
tire rolling resistance. |
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