Application examples show that it is feasible to apply the improved PSO to the weight solution of power load combination forecasting model.
通过应用实例证明，将改进的粒子群优化算法应用到电力负荷组合预测模型的权重求解是可行的。
The paper presents a short term load combined forecasting model using the simple average and weighted optimum combination principles.
文中分别应用简单平均组合与最优加权组合原理，建立了短期负荷预测的组合模型。
The combination forecasting method gives bigger weight to the models, which better conform with the variation of power load, and improves the precision. The sample calculation shows the truth.
采用组合预测法对能很好反映负荷变化规律的模型赋予较大的权重，从而提高负荷预测精度，示例计算表明组合预测法的预测精度明显高于各单一模型的预测精度。
In order to capture the effect of weather on load, this paper presents a novel thought based on ANN and trends combination short term load forecasting.
为了更好地捕捉天气对负荷的影响，文中提出了一种基于神经网络的趋势组合短期负荷预测思想和模型。
In order to capture the effect of weather on load, this paper presents a novel thought based on ANN and trends combination short term load forecasting.
为了更好地捕捉天气对负荷的影响，文中提出了一种基于神经网络的趋势组合短期负荷预测思想和模型。
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