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

页码：36 / +

页数：2

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