电力负荷

基于DSP的电力负荷运行状态监测的研究

The Research of Power Load Running Status Detecting Based on DSP

基于遗传BP网络的智能型电力负荷预测技术

The Technology of Intelligent Power Load Forecast with Genetic & BP Network

提出并设计了一种基于ARM的嵌入式电力负荷管理终端。

An embedded power load management terminal based on ARM is presented and designed in the paper .

基于灰色GM（1,1）及其改进型模型的短期电力负荷预报

Forecast of electric load based on GM ( 1,1 ) and its improved model

提出基于自组织映射（SOM）和SVM结合的电力负荷短期预测方法。

Short-term load forecasting based on SOM and SVM is proposed .

在电力负荷预测的研究中，提出了基于Agent的电力负荷预测算法，试验验证这种方法是有效的，并且采用多Agent的原理设计了一个电力负荷预测系统，实现了多种方法的负荷预测。

During the research on electric load forecasting , the electric load forecasting algorithm based on multi-agent is presented and is effective by results .

基于ARIMA模型和BP网络的电力负荷预测

Electric Load Forecasting Based on ARIMA Model and BP Network

GPRS无线通信技术在电力负荷管理系统中的应用

GPRS Wireless Communication Techniques in Power Load Management System

基于引入取舍规则的Lyapunov指数法的电力负荷预测

Electrical load forecast based on Lyapunov exponent method with rule of acceptance and rejection

电力负荷管理系统数据采集在ECM系统中的应用

Data Collection for ECM System in Management System of Electric Power Load

夏季短期电力负荷预测的MGM（1，n）建模及应用

Modeling and application of MGM ( 1 , n ) for summer short term power load forecasting

该方法巧妙运用MATLAB统计学工具箱中的现有函数，并借助可决系数和预测相对标准偏差两个定量判别指标来选择预测模型，从而能更有效地对电力负荷进行中期预测。

Using the coefficient of determination and the relative standard deviation as standard , this method can figure out a more effective forecasting model with MATLAB Statistics Toolbox .

利用改进的BP网络和RBF网络进行了短期电力负荷预测，并对训练的收敛速度和预测精度进行了分析。

By the improved BP and RBF neural networks , short-term electric load is forecast and training ( convergence ) rate and forecasting precision are analyzed .

本文采用自回归滑动平均模型（ARMA）对电力负荷进行了预测。

In this paper , autoregressive moving average model ( ARMA ) is used to forecast the power load .

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。

A short-term load forecasting model based on SVM is presented in which the parameters in SVM are optimized by Particle Swarm Optimizer ( PSO ) .

基于改进FLN的短期电力负荷预测算法

Forecasting Algorithm of Short-Term Electric Power Load Based on Improved FLN

为了提高电力负荷预报的精确度和稳定性，基于灰色理论和BP神经网络，提出了电力负荷预报方法。

To increase the accuracy and stability of the forecasting of the electric power load , this paper puts forward an estimating method of the electric power load according to the gray theory and BP neuron network .

以基于参数优化的支持向量机为建模手段来建立电力负荷模型，该算法可自动调整经验风险和VC维之间比重，并由此提高模型的泛化能力。

The parameter-optimized Support Vector Machine ( SVM ) was used to establish the power load model . The algorithm can automatically adjust the weight between the empirical risk and the VC dimension , and consequently improve the generalization ability of the model .

本文首次提出使用Kohonen神经网络解决电力负荷动态特性的聚类问题，给出了采用Kohonen神经网络进行负荷动态特性聚类的具体算法。

In this paper , a new algorithm based on Kohonen self-organization neural network is firstly presented for the characteristics clustering of dynamic loads . The analysis was carried out based on the results .

将负荷的功率和工作概率作为分类的两项指标，利用模糊自组织特征映射（SOFM）网络对负荷进行分类，并基于分类给出了电力负荷的随机估算模型。

Firstly , regarding the power and the working probability as two classification attributes , the loads are classified by using fuzzy self organizing feature map ( SOFM ) network . Then , based on the classification , the load stochastic estimation model is presented .

电力负荷监控实用化需解决的几个问题

Several problems need to solve in practice of power load monitoring

电力负荷预估的神经网络正则化及其应用

Regularization of Neural Networks for Electric Load Forecasting and its Application

小波包变换在电力负荷特征信号提取中的应用

Application of wavelet package transformation for power load feature signal extraction

电力负荷工频微机控制系统

Industrial Frequency Micro & Computer Control System for Power Load Control

实施中的电力负荷微机集中控制系统

Microcomputer Centralized Control System for Electrical Load to Put into Effect

浅析电力负荷构成及对负荷率的影响

Analyzing Electric Power Load Structure and Its Effect on Load Factor

基于粒子群优化的电力负荷灰色预测模型

Grey Model of Power Load Forecasting Based on Particle Swarm Optimization

分析了宝鸡电力负荷管理系统在电力市场营销中应能承担的重要功能。

Analyzed the important function of Baoji electric power market business .

用户信息系统信息采集范围及需求设计&也谈电力负荷管理系统重新定位及其技术解决方案

Information Measuring Range And its Demand Design of User Information System

基于蚁群聚类-Elman神经网络模型的短期电力负荷预测

Ant colony clustering-Elman neural network based model for short-term load forecasting