针对累积式自回归-移动平均模型在现代城市降温负荷预测中准确性不高的问题，提出一种双因子累积式自回归-移动平均模型，并用两种模型进行预测。经对比后发现，新模型通过引入平均温度算子，有效提高了城市降温负荷预测的准确性，并对现代城市有较好的普适性。%A dual-factor auto-regressive integrated moving average model (ARIMA model) has been established to tentatively improve the low accuracy of the ARIMA model in forecasting modern urban cooling loads, followed by a simultaneous predication testing by these two models. A final comparison between the two prediction results shows that the new model, by introducing an average temperature operator to the forecasting process, has effectively improved the urban cooling load forecasting accuracy with a universal applicability on its former basis of an ARIMA model.
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