The combination forecasting model of generalized weighted proportional means which to overcome the inadequacy of traditional single market forecasting method, was used to forecast market demands.
运用广义加权平均组合预测模型进行市场需求预测，以克服传统的单一市场预测方法的不足。
According to the characteristics of heat supply and the demands of energy-saving control, heat load forecasting based on RBF neural network and time series crossover is proposed.
针对供热过程的特点及节能控制的需要，提出基于RBF神经网络的时间序列交叉供热负荷预报法。
According to the characteristics of heat supply and the demands of energy-saving control, heat load forecasting based on RBF neural network and time series crossover is proposed.
针对供热过程的特点及节能控制的需要，提出基于RBF神经网络的时间序列交叉供热负荷预报法。
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