Application of Syntactic Pattern Recognition Methods for Electrical Load Forecasting

被引：2
|
作者：
Flasinski, Mariusz [1 ]
Jurek, Janusz [1 ]
Peszek, Tomasz [1 ]
机构：
[1] Jagiellonian Univ Cracow, Informat Technol Syst Dept, Ul Prof St Lojasiewicza 4, PL-30348 Krakow, Poland
来源：
PROCEEDINGS OF THE 9TH INTERNATIONAL CONFERENCE ON COMPUTER RECOGNITION SYSTEMS, CORES 2015 | 2016年 / 403卷
关键词：
STRING PATTERNS; INFERENCE; MODEL; HELP; TOOL;
D O I：
10.1007/978-3-319-26227-7_56
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Electrical load forecasting is an important problem concerning safe and cost-efficient operation of the power system. Although many techniques are used to predict an electrical load, a research into constructing more accurate methods and software tools is still being conducted over the world. In this paper an experimental application for improving an accuracy of an electrical load prediction is presented. It is based on the syntactic pattern recognition approach and FGDPLL(k) string automata. The application has been tested on the real data delivered by one of the Polish electrical distribution companies.
引用
收藏
页码：599 / 607
页数：9
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