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篇名
Load Forecasting Based on Optimized Random Forest Algorithm in Cloud Environment
並列篇名
Load Forecasting Based on Optimized Random Forest Algorithm in Cloud Environment
作者 Xin Sui (Xin Sui)Hailong Zhao (Hailong Zhao)Honghua Xu (Honghua Xu)Xiaolong Song (Xiaolong Song)Dan Liu (Dan Liu)
英文摘要

To solve the problem of unbalanced resource load in cloud data center, a resource load forecasting method which is based on random forest model from the perspective of resource load forecasting is proposed in the paper. This method combines genetic algorithm with random forest algorithm to solve the problem that random forest algorithm can not determine the combination of parameter in order to obtain the optimum forecasting effect. The results of experiment show that compared with the super parametric method of random forest model, which is optimized by random search, the one optimized by genetic algorithm proposed in this paper has higher forecasting accuracy.

 

起訖頁 013-026
關鍵詞 random forestload balancingsuper parametric optimization
刊名 電腦學刊  
期數 202406 (35:3期)
該期刊-上一篇 Empirical Study on Poor-Rich Disparities Based on College Campus Consumption Data
該期刊-下一篇 Applying LSTM Model to Predict the Japanese Stock Market with Multivariate Data
 

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