题目
英语翻译
因为是新手,所以没有财富可悬赏,请大家多多见谅
In previous work,we applied artificial neural networks (ANN) for short term load forecasting using real load and weather data from the Hydro-Quebec databases where three types of variables were used as inputs to the neural network:(a) hour and day indicators,(b) weather related inputs and (c) historical loads.In general,for forecasting with a lead time of up to a few days ahead,load history (for the last few days) is not available,and therefore,estimated values of this load are used instead.However,a small error in these estimated values may grow up dramatically and lead to a serious problem in load forecasting since this error is fed back as an input to the forecasting procedure.In this paper,we demonstrate ANN capabilities in load forecasting without the use of load history as an input.In addition,only temperature (from weather variables) is used,in this application,where results show that other variables like sky condition (cloud cover) and wind
因为是新手,所以没有财富可悬赏,请大家多多见谅
In previous work,we applied artificial neural networks (ANN) for short term load forecasting using real load and weather data from the Hydro-Quebec databases where three types of variables were used as inputs to the neural network:(a) hour and day indicators,(b) weather related inputs and (c) historical loads.In general,for forecasting with a lead time of up to a few days ahead,load history (for the last few days) is not available,and therefore,estimated values of this load are used instead.However,a small error in these estimated values may grow up dramatically and lead to a serious problem in load forecasting since this error is fed back as an input to the forecasting procedure.In this paper,we demonstrate ANN capabilities in load forecasting without the use of load history as an input.In addition,only temperature (from weather variables) is used,in this application,where results show that other variables like sky condition (cloud cover) and wind
提问时间:2021-03-16
答案
在以往的工作中,我们运用人工神经网络(ANN)为短期负荷预测实际负载和天气的地方Hydro-Quebec数据库数据的三种类型的变量作为输入与神经网络:(一)时指标(b)天气相关的输入(c)历史负荷.一般来说,对于预测与领先的时间...
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