Accurate mid-long term load forecasting can improve the economic and social benefits of power system.
准确的中长期负荷预测能够提高电力系统的经济效益和社会效益。
Case study shows that this method is more accurate and faster than single grey prediction and single neural network method. It is a useful method for long term load forecasting.
最后采用我国某省年用电量的预测的算例表明该方法的预测精度优于单一的灰色预测和单一的神经网络预测方法，为电力系统长期负荷预测提供了一种有用的方法。
Because the medium and long term load forecasting in distribution network is affected by many uncertain factors, up to now, no methods can obtain the satisfying forecasting results at all instances.
由于配电网中长期负荷预测，会受到很多不确定因素的影响。因此，到目前为止，还没有哪一种方法能保证在任何情况下都能获得满意的预测结果。
In application of neural networks based short-term load forecasting model, the main problems are over many training samples, thus resulting long training time and slow convergence speed.
在神经网络负荷预测实际应用中，突出的问题是训练样本大、训练时间长、收敛速度慢。
In this paper, the application of artificial neural network (ANN) for short - term load forecasting and mid - long - term load forecasting are analyzed and compared.
本文分别对人工神经网络(ANN)在短期负荷预测和中长期负荷预测中的应用进行了分析、对比。
Aiming at the features of medium and long-term load forecasting, a comprehensive model for medium and long-term load forecasting based on Analytic Hierarchy Process (AHP) was put forward.
针对中长期电力负荷预测特点，提出了一种基于AHP(层次分析法)的中长期电力负荷预测综合模型。
An improved model based on RBF neural network for medium and long-term load forecasting is presented. The feasibility and validity o...
实际算例的分析表明，所提出的基于RBF神经网络的缺损数据处理方法和改进的中长期负荷预测模型是可行和有效的。
Gas load forecasting include: long-term, middle-term, short-term, very short-term load forecasting.
燃气负荷预测包括长期负荷预测、中期负荷预测、短期负荷预测及超短期负荷预测。
Gas load forecasting include: long-term, middle-term, short-term, very short-term load forecasting.
燃气负荷预测包括长期负荷预测、中期负荷预测、短期负荷预测及超短期负荷预测。
应用推荐