| Tread dimension prediction model based on mixed kernel function and PLS |
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| DOI： |
| Key Words: mixed kernel function，partial least squares；tread dimension；prediction model |
| Author Name | Affiliation | | MA Tie jun | South China University of Technology | | OUYANG Lai | South China University of Technology |
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| Abstract: |
| In order to accurately predict the tread dimension in the course of production，a prediction model based on mixed kernel function and partial least squares(PLS) was constructed by analyzing the tread processing technique.Firstly，auxiliary variables were mapped into the high dimension space，then a prediction model was constructed using linear modeling method in this high dimension space，finally the non-linear prediction model was obtained from it through non-linear function mapping.The results showed that the prediction model had good learning and generalization ability，and excellent accuracy，which could meet the requirement of production.
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