scholarly journals On Neural Network Modeling of Main Steam Temperature for Ultra - supercritical Power Unit with Load Varying

2016 ◽  
Author(s):  
Xifeng Guo ◽  
Jingtao Huang ◽  
Lijie Wang ◽  
Jia Zhang
Keyword(s):  
Neural Network ◽  
Power Unit ◽  
Network Modeling ◽  
Neural Network Modeling ◽  
Steam Temperature ◽  
Main Steam

Neural Network Modeling For Main Steam Temperature System

2014 ◽  
Vol 69 (3) ◽  
Author(s):  
N. A. Mazalan ◽  
A. A. Malek ◽  
Mazlan A. Wahid ◽  
M. Mailah
Keyword(s):  
Neural Network ◽  
Dead Time ◽  
Steam Pressure ◽  
Neural Network Modeling ◽  
Steam Temperature ◽  
Power Plant Boiler ◽  
Plant Data ◽  
Main Steam ◽  
Generator Output ◽  
Plant Boiler

Main Steam Temperature (MST) is non-linear, large inertia, long dead time and load dependant parameters. The paper present MST modeling method using actual plant data by utilizing MATLAB's Neural Network toolbox. The result of the simulation showed the MST model based on actual plant data is possible but the raw data need to be pre-processed for better output. Generator output, total main steam flow, main steam pressure and total spray flow are four main parameters affected the behavior of MST in coal fired power plant boiler.

Water quality parameter forecast based on grey neural network modeling

2009 ◽  
Vol 29 (6) ◽  
pp. 1529-1531 ◽  
Author(s):  
Wei-ren SHI ◽  
Yan-xia WANG ◽  
Yun-jian TANG ◽  
Min FAN
Keyword(s):  
Neural Network ◽  
Water Quality ◽  
Network Modeling ◽  
Quality Parameter ◽  
Water Quality Parameter ◽  
Neural Network Modeling

ε-Insensitive Criterion and Structure Risk Based Radius-basis-function Neural-network Modeling

2012 ◽  
Vol 34 (6) ◽  
pp. 1414-1419
Author(s):  
Qing-bing Sang ◽  
Zhao-hong Deng ◽  
Shi-tong Wang ◽  
Xiao-jun Wu
Keyword(s):  
Neural Network ◽  
Basis Function ◽  
Network Modeling ◽  
Neural Network Modeling
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