A joint of adaptive predictors for electric load forecasting

被引：0

作者：

Nastac, Dumitru Iulian ^{[1
]}

Ulmeanu, Anatoli Paul ^{[1
]}

Tuduce, Rodica ^{[1
]}

Cristea, Paul Dan ^{[1
]}

机构：

[1] Univ Politehn Bucuresti, Bucharest, Romania

来源：

2013 20TH INTERNATIONAL CONFERENCE ON SYSTEMS, SIGNALS AND IMAGE PROCESSING (IWSSIP 2013) | 2013年

关键词：

forecasting; artificial neural networks; retraining; electric load; ALGORITHM; MODEL;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This work describes a new approach of the adaptive retraining model for data forecasting. This time, six predictors are simultaneously employed in order to produce a better forecasting for electric load. By doing so, the new forecasting system eliminates iterative simulation. The set of predictors is regularly trained in order to be adjusted to the latest modifications of the input data. The new approach could be useful as a forecasting tool for a large variety of signals.

引用

页码：51 / 54

页数：4

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