The hybrid algorithm can be effectively used in short time load forecasting of the power system.
该算法可有效用于电力系统的短期负荷预测。
Based on the theoretical study and analysis of super short time load forecasting, this paper proposed voltage and reactive power control strategy based on super short time forecasting.
通过对超短期负荷预测理论的分析和研究，提出了基于超短期负荷预测技术电压无功控制策略。
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.
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。
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。
The principle of extension short-time load forecast was put forward, that is forecasting unknown load point by adding information of new load point to the point, the load was known.
提出了扩展短期负荷预测的原理，即在已知当日部分负荷的条件下，引入最新获得的负荷相关信息，预测当日未知的多点负荷。
There are traditional model methods of forecasting short-term load, such as time series, regression analysis, and so on.
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。
Based on local linear prediction model of chaotic time series, short-term load forecasting method on multi-embedding dimension is presented.
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。
An improved method for short term electric load forecasting is presented. It is based on time series methods and fuzzy logic techniques.
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。
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.
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.
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。
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