.png){kind=icon}
返回
Multiple Kernel Learning-Based Transfer Regression for Electric Load Forecasting
.png){kind=icon}
PRE
AI
DOI：10.1109/TSG.2019.2933413.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Electric load forecasting, especially short-term load forecasting (STLF), is becoming more and more important for power system operation. We propose to use multiple kernel learning (MKL) for residential electric load forecasting which provides more flexibility than traditional kernel methods. Computation time is an important issue for short-term forecasting, especially for energy scheduling. However, conventional MKL methods usually lead to complicated optimization problems. Another practical issue for this application is that there may be a very limited amount of data available to train a reliable forecasting model for a new house, while at the same time we may have historical data collected from other houses which can be leveraged to improve the prediction performance for the new house. In this paper, we propose a boosting-based framework for MKL regression to deal with the aforementioned issues for STLF. In particular, we first adopt boosting to learn an ensemble of multiple kernel regressors and then extend this framework to the context of transfer learning. Furthermore, we consider two different settings: homogeneous transfer learning and heterogeneous transfer learning. Experimental results on residential data sets demonstrate that forecasting error can be reduced by a large margin with the knowledge learned from other houses.
Keyword:
Kernel
Boosting
Load forecasting
Forecasting
Predictive models
Load modeling
Computational modeling
Electric load forecasting
boosting
multiple kernel learning
transfer learning
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
9.8
论文数:
5.7K
被引数:
4.3W
机构
引用论文
.png){kind=icon}
分享收藏A Strategy for Short-Term Load Forecasting by Support Vector Regression Machines基于支持向量回归机的短期负荷预测策略
PREAI
分享收藏分享收藏Short-Term Residential Load Forecasting Based on LSTM Recurrent Neural Network基于LSTM循环神经网络的短期住宅负荷预测
PREAI
分享收藏
查看更多内容