8-------Short-term Electricity Load Forecasting using Time Series and Ensemble Learning Methods - 代码天地

8-------Short-term Electricity Load Forecasting using Time Series and Ensemble Learning Methods

其他 2018-12-09 09:10:59 阅读次数: 0

就是四种方法+残差分析

讨论了四种不同的方法。并进行了比较，即季节自回归滑动平均（SARIMA）与EXOGE-季节性自回归滑动平均

随机变量（SARIMAX）、随机森林（RF）和梯度提升回归树（GBRT）。预测性能每个模型通过两个度量来评估，即平均绝对值。百分比误差（MAPE）和均方根误差（RMSE）。研究结果表明，GBRT模型优于其他人提前24小时进行预测。

残差分析：

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转载自blog.csdn.net/qq_34514046/article/details/84844231

8-------Short-term Electricity Load Forecasting using Time Series and Ensemble Learning Methods

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