By Topic

A cascaded neural network and its application to modelling power plant pollutant emission

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)
Kang Li ; Dept. of Mech. & Manuf. Eng., Queen''s Univ., Belfast, UK ; Thompson, S.

Pollutant emission in power generation plant, especially NOx emission, has attracted much attention in the last ten years. For an operating plant, development of an advanced control system is essential for pollutant emission reduction. System modelling is an important stage in emission control. In this paper, a cascading neural network is used to model the NOx emission in a coal-fired power generation plant. This type of neural network has more connections than that found in the layered feedforward neural network. Algorithm for training this type of neural network is suggested and then it is used to build a NOx emission model for a coal-fired power generation plant. Simulation results show the merits of this type of neural network

Published in:

Intelligent Control and Automation, 2000. Proceedings of the 3rd World Congress on  (Volume:2 )

Date of Conference:

2000