Load forecasting using artificial neural networksand support vector regression

被引：0
|
作者：
De Rocco, Silvio Michel [1 ,3 ,4 ]
Aoki, Alexandre Rasi [2 ,4 ]
Lamar, Marcus Vinicius [3 ]
机构：
[1] Univ Fed Parana, Dept Elect Engn, UFPR Polytech Ctr, POB 19011, BR-80060000 Curitiba, Parana, Brazil
[2] LACTEC, Inst Technol Dev, UFPR Polytech Ctr, BR-81531980 Curitiba, Brazil
[3] Parana Energy Co, BR-81200240 Curitiba, Parana, Brazil
[4] Brasilia Fed Univ, Dept Comp Sci, BR-70919970 Curitiba, Parana, Brazil
来源：
PROCEEDINGS OF THE 7TH WSES INTERNATIONAL CONFERENCE ON POWER SYSTEMS: NEW ADVANCES IN POWER SYSTEMS | 2007年
关键词：
load forecasting; artificial neural networks; support vector regression;
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
This paper describes a short term load forecasting system using two different techniques of Artificial Intelligence: Recurrent Artificial Neural Networks and Support Vector Regression. A brief analysis of the load over the distribution systems connection points in Brazilian Parana States is also done.
引用
收藏
页码：36 / +
页数：2
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