Close category search window
 

Prediction of the NOx emissions from thermal power plant based on support vector machine optimized by genetic algorithm

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Jianguo Zhou ; Sch. of Bus. & Adm., North China Electr. Power Univ., Baoding, China ; Huaitao Liang

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.

Published in:
Information and Financial Engineering (ICIFE), 2010 2nd IEEE International Conference on

Date of Conference: 17-19 Sept. 2010

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2013 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.