Product Sale Forecast Based on Support Vector Machine Optimized by Cross Validation and Grid Search
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    Abstract:

    Considering various factors affecting automobile sales, the penalty coefficient and kernel function parameters of support vector machine are optimized by cross validation and grid search, and a prediction model suitable for automobile sales is established. The simulation results show that the forecasting effect of the improved support vector machine optimized automobile sales forecasting model is better than that of the current model adopted by a company. The model has higher forecasting accuracy and greater credibility, and can provide more accurate sales forecasting reference for enterprise decision-making level.

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张文雅,范雨强,韩华,张斌,崔晓钰.基于交叉验证网格寻优支持向量机的产品销售预测.计算机系统应用,2019,28(5):1-9

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History
  • Received:November 28,2018
  • Revised:December 18,2018
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  • Online: May 05,2019
  • Published: May 15,2019
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