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。
The accuracy of power load forecasting is significant to the reasonable planning and construction of power system.
电力负荷预测的准确性对于电力系统的合理规划与建设意义重大。
Therefore, the key is to improve the accuracy of load forecasting.
因此，负荷预测的关键是提高准确度。
A new load forecasting method based on intrinsic error evaluation is proposed.
提出了一种基于内蕴误差评价的电力系统短期负荷预报方法。
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。
This paper proposes a novel spatial load forecasting (SLF) method for distribution planning.
文章提出了一种新颖的配电网空间负荷预测模型。
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。
The main factor influencing the accuracy of load forecasting is the uncertainty of original data.
影响负荷预测准确性的最主要因素是原始数据的不确定性。
On the basis of analyzing the character of subarea load forecasting, a general model is established.
在分析分区预测特点的基础上建立了一个通用模型。
Power system load forecasting using stochastic system state model identification technique is proposed.
本文将随机系统状态模型辨识技术用于电力系统负荷预报。
On the basis of the system load forecasting, a method of node load pattern forecasting has been presented.
在总体负荷预报的基础上提出了节点负荷模式预报的方法。
The paper also researches the power load forecasting and gives an analysis of a short forecasting algorithm.
本文还研究了电力负荷预测算法，并给出了一种电力负荷短期预测算法的详细分析。
The forecasting result shows that season and trend mode is an effective and feasible load forecasting method.
预测结果表明季节和趋势预测模型是一种有效和可行的负荷预测方法。
Grasping the change rule and trend of power load characteristic is the key to establish load forecasting model.
掌握电力负荷特性的变化规律和发展趋势是建立负荷预测模型的关键。
According to the result, envelopes of load forecasting curve under certain confidence level can also be obtained.
基于该结果，还能求取某一置信水平下的预测负荷曲线的包络线。
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。
In this paper, an adaptive bus load forecasting approach based on the thinking of virtual forecasting is proposed.
文章提出了一种基于虚拟预测思想的自适应母线负荷预测技术。
Electrical load forecasting is a complicated multilevel system including dimensions of space, time, attributes, etc.
电力负荷预测是一个包含空间、时间、属性等多维度多级别的复杂体系。
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。
Power system load forecasting process, short-term forecasting, considering the weather, human comfort and other factors.
说明：电力系统负荷预测程序，短期预测，考虑天气、人体舒适度等因素。
According to the trait of the power load forecasting. this paper proposes the genetic neural network load forecasting model.
根据电力负荷预测的特点，提出遗传神经网络负荷预测模型。
The time series analysis is proposed for load forecasting of power-generating and power transmission programming in power systems.
本文提出用于电力系统发电规划和输电规划负荷预测的时间序列分析法。
A load forecasting system of district power network is researched and developed to meet the requirement of district dispatch center.
根据地区调度中心的需求，研究并开发了一个地区电网负荷预测系统。
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。
An example of the algorithm's application in electric power system load forecasting is shown and compared with standard BP algorithm.
文中给出了这种算法在电力系统负荷预测中的实际应用，并与标准BP算法作了比较。
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。
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。
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