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。
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。
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。
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。
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 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。
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。
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。
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 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。
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。
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。
Short-term load forecasting is the foundation of Auto Generation Control (AGC). And it is needed in running and economic distributing of power system.
超短期负荷预测将成为AGC（自动发电控制）实用化的基础，同时也是动态经济调度和电力市场运行所需的基本信息。
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 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。
In addition, the fuzzy functions for specified factors are built, and in ultra short-term load forecasting the similar load days are extracted by clustering analysis.
此外建立了一些特定因素的模糊函数，在超短期负荷预测过程中采用了聚类分析法提取负荷相似日。
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.
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。
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。
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。
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。
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