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中文摘要：
电力负荷预测的复杂性、不确定性使传统的单一预测模型难以获得精确的结果。为提高电力负荷预测准确度,构建了一种组合预测模型。该模型综合灰色递阶模型、＂S＂曲线模型和逐步回归模型预测结果的过程中引入灰色关联度作为确定组合预测权重的依据,综合协调各个结果,得到更为合理的预测值。
英文摘要：
Due to the complication and uncertainty of power load forecasting, it can not rely on single traditional forecasting model to get the accurate result. To solve the problem, a combined forecasting model was constructed which synthesizes the forecasting results of the grey hierarchical model, the “S” curve model, and the stepwise regression model and uses the grey relational grade to determine each weight of them. The forecasting result was more accurate with this new model.
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Improved wavelet neural network combined with particle swarm optimization algorithm and its applicat
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