This paper has presented a new approach for short-term load forecasting.
提出了一种新的短期电力负荷预报方法。
Short-term load forecasting is of great importance for electric power systems.
短期电力负荷的预测对电力系统具有重要的意义。
Linear regression analysis is a most common method for mid term load forecasting.
线性回归是电力系统中期负荷预测的常用方法。
This paper presents a fuzzy neural network approach to short term load forecasting.
提出了一种用于短期电力负荷预报的模糊神经网络方法。
A medium and short term load forecasting system is designed for Guilin Power Network.
设计了一套桂林电网中短期负荷预测系统。
A short term load forecasting software system for Northwest Grid is presented in this paper.
本文介绍了西北电网短期负荷预测软件系统。
A reduced dimensions method applying neural network is proposed for short term load forecasting.
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。
So the study of short-term load forecasting has been paid enough attentions in the past decades.
因此，短期负荷预测方法的研究一直为人们所重视。
In this paper we propose a method for short-term load forecasting using artificial neural network.
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。
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。
Wavelet neural network short term load forecasting, neural network model and BP learning algorithm.
小波神经网络实现短期电力负荷预测，神经网络模型及其BP学习算法。
To improve prediction precision is the most radical objective in short term load forecasting (STLF).
提高预测精度是短期负荷预测的基本目标。
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。
This paper presents a new short-term load forecasting method based on resource-allocating network (RAN).
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。
A novel method called load derivation is introduced for ultra-short term load forecasting of power system.
负荷求导法是超短期电力负荷预测的一种新方法。
As an illustrative application example, the numerical result of the medium-term load forecasting is given.
还利用提出的改进算法对某省中期负荷进行了预测，算例结果表明了该算法的有效性。
The paper presents an immune clustering RBF neural network (ICRBFNN) model for short-term load forecasting.
提出了一种免疫聚类径向基函数神经网络(ICRBFNN)模型来预测电力系统短期负荷。
Therefore, how to improve the forecasting precision is the emphasis on the study of short-term load forecasting.
因此，关于如何提高预测精度的问题，一直是短期负荷预测研究的重点问题。
A new gray theory self-correcting model is applied to the error correct of Short-term Load Forecasting Technique.
本文把一种新的灰色理论自修正模型应用到负荷预测的误差校正中。
A recurrence algorithm of dynamic economic dispatching coupled with very short term load forecasting is presented.
本文提出一个与超短期负荷预报结合在一起的动态经济调度递推算法。
This paper presents a new algorithm for short term load forecasting based on the deterministic annealing technique.
首次将确定性退火方法用于短期负荷预测领域。
Seeking the causes of the chaos of load records is important to im prove the accuracy of short- term load forecasting.
研究负荷记录混沌的成因，对于提高短期负荷预报的准确率是必要的。
A hybrid method based on chaos and neural network was used in the study of the electric power system 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。
The architecture and implementation of an auto-operating short-term load forecasting system for Shenzhen power network is resumed.
概述了深圳电网自动运行的短期负荷预测系统的结构及其实现方案。
Accurate short-term load forecasting plays an essential role in planning, economical scheduling and security analysis in production.
精确的负荷预测对于电力系统的生产安排、经济调度和安全分析都起着十分重要的作用。
The short-term load forecasting (STLF) of electric system is one of the important routines for power dispatch and utility departments.
电力系统短期负荷预测是电力系统调度运营和用电服务部门的重要日常工作之一。
Practical operation results show that the cluster analysis method can considerably improve the accuracy of short-term load forecasting.
实际运行结果表明：利用聚类分析法进行负荷短期预测，短期负荷预测的精度大大提高。
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。
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。
A short-term load forecasting model based on SVM is presented in which the parameters in SVM are optimized by Particle Swarm Optimizer (PSO).
文章提出了PSO优化参数的SVM回归预测模型，并将其用于短期电力负荷预测。
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