The nature of statistical learning theory
The nature of statistical learning theory
An introduction to differential evolution
New ideas in optimization
An Automated System for Prediction of Icing on the Road
ICCS '02 Proceedings of the International Conference on Computational Science-Part III
A distributed PSO-SVM hybrid system with feature selection and parameter optimization
Applied Soft Computing
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The road icing is an adverse weather condition leads to dangerous driving conditions with consequential effects on road transportation. A numerical road icing predication approach is employed for automatic prediction of road icing conditions for Shiyan City. The approach is derived from the support vector machine (SVM). To improve the classification accuracy for road icing prediction, a modified differential evolution (DE) is employed to simultaneously select features. With the data from 1980 to 2006, using the proposed approach, the road icing models for the city are created, which have been used for the prediction for Shiyan City from 2007 to 2008. The results have shown feasibility and effectiveness of the forecast approach.