Short-Term Load Forecasting Based on Kernel Conditional Density Estimation

Grzegorz DUDEK

首页> 外文期刊>Przeglad Elektrotechniczny >Short-Term Load Forecasting Based on Kernel Conditional Density Estimation

【24h】

Short-Term Load Forecasting Based on Kernel Conditional Density Estimation

机译：基于核条件密度估计的短期负荷预测

获取原文

获取原文并翻译 | 示例

获取外文期刊封面封底 >>

开具论文收录证明 >>

文献代查 >>

页面导航

摘要
著录项
相似文献
相关主题

摘要

A short-term load forecasting model based on the kernel estimation of the conditional probability density distribution is proposed. The pattern vector of the load time series sequence can be treated as the multivariate random variable whose value determines the pattern component values of the next sequence, which is forecasted. Probability density functions are obtained from historical load time series by means of nonparametric density estimation. This approach uses the product kernel estimators. The kernel function smoothing parameters are determined using cross-validation procedure. The suitability of the proposed approach is illustrated through applications to real load data.

机译：提出了一种基于条件概率密度分布核估计的短期负荷预测模型。加载时间序列序列的模式向量可以视为多元随机变量，其值确定了预测的下一个序列的模式分量值。概率密度函数是通过非参数密度估计从历史负载时间序列获得的。这种方法使用乘积核估计器。使用交叉验证过程确定内核函数平滑参数。通过对实际载荷数据的应用说明了所提出方法的适用性。

著录项

来源
《Przeglad Elektrotechniczny》 |2010年第8期|P.164-167|共4页
作者
Grzegorz DUDEK;
展开▼
作者单位

Czeestochowa University of Technology, Institute of Power Engineering, al. Armii Krajowej 17, 42-200 Czestochowa, Poland;

展开▼
收录信息
原文格式 PDF
正文语种 eng
中图分类
关键词
short-term load forecasting; kernel density estimation; nonparametric regression;

机译：短期负荷预测;核密度估计;非参数回归;

相似文献

外文文献
中文文献
专利

1. Short-term load probabilistic forecasting based on quantile regression convolutional neural network and Epanechnikov kernel density estimation [J] . Hui He, Junting Pan, Nanyan Lu, Energy Reports . 2020,第4期

机译：基于分位数回归卷积神经网络和EPANECHNIKOV内核密度估计的短期负荷概率预测
2. Short-term forecasting and uncertainty analysis of wind power based on long short-term memory, cloud model and non-parametric kernel density estimation [J] . Gu Bo, Zhang Tianren, Meng Hang, Renewable energy . 2021,第Feba期

机译：基于长短短期记忆，云模型和非参数核密度估计的风电的短期预测与不确定度分析
3. Short-term power load probability density forecasting based on Yeo-Johnson transformation quantile regression and Gaussian kernel function [J] . He Yaoyao, Zheng Yaya Energy . 2018,第JULa1期

机译：基于Yeo-Johnson变换分位数回归和高斯核函数的短期电力负荷概率密度预测
4. Short-term wind speed forecasting based on non-parametric kernel density estimation [C] . Jiegui Zhou, Jia Hongjie, Zhen Tian, IEEE Innovative Smart Grid Technologies - Asia;ISGT Asia . 2012

机译：基于非参数核密度估计的短期风速预测
5. The Kernel Method of Density Estimation With Applications in Discrimination, Selection of Features, and Conditional and Marginal Distributions [D] . Girdwood Aitken, Colin Graeme. 1979

机译：密度估计的核方法及其在判别，特征选择以及条件和边际分布中的应用
6. An extended Weight Kernel Density Estimation model forecasts COVID-19 onset risk and identifies spatiotemporal variations of lockdown effects in China [O] . Wenzhong Shi, Chengzhuo Tong, Anshu Zhang, 2021

机译：扩展重量核密度估计模型预测Covid-19发病风险并识别中国锁定效应的时空变化
7. Using conditional kernel density estimation for wind power density forecasting [O] . Jooyoung Jeon, James W. Taylor 2016

机译：利用条件核密度估计进行风电功率密度预测
8. Neutral network based technique for short-term forecasting of anomalous load periods [R] . Sforna, M. , Lamedica, R. , Prudenzi, A. , 1995

机译：基于中性网络的异常负荷期短期预测技术

Short-Term Load Forecasting Based on Kernel Conditional Density Estimation

摘要

著录项

相似文献

相关主题

期刊订阅