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• W2232431322 startingPage "1564" @default.
• W2232431322 abstract "It is very helpful for power system operation to assess and forecast the uncertainty of the load forecasting. The improved credibility assessment index of the short-term load forecasting results is presented to assess the uncertainty in this study. The forecasting method for credibility of short-term load forecasting is also proposed by adopting genetic algorithm-based back propagation neural network. In the case study, it is proved that the improved credibility assessment can evaluate the short-term load forecasting results and the forecasting methods. Meanwhile, the credibility forecasting can contribute to optimise reserve capacity in power system scheduling." @default.
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• W2232431322 date "2015-10-01" @default.
• W2232431322 modified "2023-09-26" @default.
• W2232431322 title "Credibility forecasting in short‐term load forecasting and its application" @default.
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• W2232431322 doi "https://doi.org/10.1049/iet-gtd.2014.0729" @default.
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