DocumentCode
2670125
Title
Prediction of the NOx emissions from thermal power plant based on support vector machine optimized by genetic algorithm
Author
Zhou, Jianguo ; Liang, Huaitao
Author_Institution
Sch. of Bus. & Adm., North China Electr. Power Univ., Baoding, China
fYear
2010
fDate
17-19 Sept. 2010
Firstpage
651
Lastpage
654
Abstract
With the development of thermal power industry, statistics on the NOx emissions become important. In this paper, based on the traditional support vector machine model, we establish support vector machine model optimized by genetic algorithm, improve the prediction accuracy of SVM model. Use the NOx emissions data from 1995 to 2009, predict the NOx emissions from thermal power plant in the year of 2010, and verify the reasonableness of the GA-SVM model.
Keywords
genetic algorithms; nitrogen compounds; pollution; power engineering computing; support vector machines; thermal power stations; GA-SVM model; NOx; NOx emission prediction; genetic algorithm; prediction accuracy; support vector machine; thermal power plant; Gallium; Genetic algorithms; Mathematical model; Optimization; Power generation; Predictive models; Support vector machines; NOx emissions; genetic algorithm; support vector machine; thermal power plant;
fLanguage
English
Publisher
ieee
Conference_Titel
Information and Financial Engineering (ICIFE), 2010 2nd IEEE International Conference on
Conference_Location
Chongqing
Print_ISBN
978-1-4244-6927-7
Type
conf
DOI
10.1109/ICIFE.2010.5609441
Filename
5609441
Link To Document