因此，短期负荷预测方法的研究一直为人们所重视。
So the study of short-term load forecasting has been paid enough attentions in the past decades.
提出一种时间序列算法和模糊逻辑技术相结合的电力系统短期负荷预测方法。
An improved method for short term electric load forecasting is presented. It is based on time series methods and fuzzy logic techniques.
基于混沌时间序列的局域线性预测模型，提出了多嵌入维的短期负荷预测方法。
Based on local linear prediction model of chaotic time series, short-term load forecasting method on multi-embedding dimension is presented.
计算结果表明，提出的短期负荷预测方法是简单、快速并精确的，可在个人计算机上实现。
Results show that short-term load forecasting by the developed method is sample, fast and accurate, which can be implemented on a personal computer.
研究了负荷时间序列波动性，考虑方差时变特征，提出了基于随机波动（SV）模型的短期负荷预测方法。
The volatility of load time series is analyzed, and the short-term load forecasting based on SV(Stochastic Volatility) models is presented with the consideration of the time-varying characteristics.
针对电力系统负荷变化具有明显的分形自相似性的特点，提出了一种新的基于弹性系数的短期负荷预测方法。
A new method of short time load forecasting on the base of elasticity coefficient is put forward according to the characteristic of obvious fractal self similarity of load change in power system.
提出一种基于资源分配网络 （ resource-allocating network，RAN）的短期负荷预测方法。
This paper presents a new short-term load forecasting method based on resource-allocating network (RAN).
提出一种采用神经网络进行电力系统短期负荷预测的降维方法。
A reduced dimensions method applying neural network is proposed for short term load forecasting.
提出了一种将混沌和神经网络相结合的方法用于短期负荷预测。
A hybrid method based on chaos and neural network was used in the study of the electric power system short-term load forecasting.
本文提出了一种应用人工神经网络进行电力系统短期负荷预测的方法。
In this paper we propose a method for short-term load forecasting using artificial neural network.
电力系统短期负荷预测使用的方法有传统建模方法，诸如时间序列、回归分析等方法。
There are traditional model methods of forecasting short-term load, such as time series, regression analysis, and so on.
提出了一种基于决策树技术的短期电力负荷预测新方法，能有效地考虑非负荷因素对短期负荷预测的影响。
This paper proposes a new short-term load forecasting method based on decision-tree approaches, which could efficiently take the non-load factors' influences into account.
利用相应的BP算法对未来24小时负荷进行短期预测，该方法充分发挥了神经网络处理非线性问题的能力。
The corresponding BP algorithm, which brings its ability of processing non-linear problem into full play, is used to forecast the short-term load in future 24 hours.
最后通过模糊推理策略预测日最大负荷和日最小负荷。实际算例表明，所提出的方法能够提高短期负荷预测的精度。
The results of practical calculation examples show that the accuracy of forecasted short-term load can be improved by the proposed method.
对于受不确定因素影响的短期电力负荷，提出了一种基于相似日的神经网络预测方法。
For the short -term electric power load with uncertainty influence factors, we put forward the load forecasting method using ANN based on similar historical day.
提出了一种交替梯度算法对径向基函数(RBF)神经网络的训练方法进行改进，并将之运用于电力系统短期负荷预测。
This paper proposes one kind of alternant gradient algorithm for improving the training of RBF neural network, which is applied to short-term electric load.
负荷求导法是超短期电力负荷预测的一种新方法。
A novel method called load derivation is introduced for ultra-short term load forecasting of power system.
首次将确定性退火方法用于短期负荷预测领域。
This paper presents a new algorithm for short term load forecasting based on the deterministic annealing technique.
进行实际短期负荷预测时，对某个固定地区，用不同预测方法可能得到不同的预测结果。
For a given electric power utility. various forecasting results can be obtained by using different models.
经实际电网超短期负荷预测检验，论文所提方法能有效提高超短期负荷预测精度。
The real power system ultra-term load forecasting proved that effectiveness of the method from the paper in the improvement of the precision of ultra-short term load forecasting.
经实际电网超短期负荷预测检验，论文所提方法能有效提高超短期负荷预测精度。
The real power system ultra-term load forecasting proved that effectiveness of the method from the paper in the improvement of the precision of ultra-short term load forecasting.
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