Prediction of NOX emission for coal-fired boilers based on deep belief network-Reference-Cited by-同舟云学术

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Prediction of NOX emission for coal-fired boilers based on deep belief network

Published:2018-11 Issue: Volume:80 Page:26-35
ISSN:0967-0661
Container-title:Control Engineering Practice
language:en
Short-container-title:Control Engineering Practice

Author:

Wang Fang,Ma Suxia,Wang He,Li Yaodong,Zhang Junjie

Funder

Thermal Power Unit Energy-Saving Monitoring Key Technologies Research Program in Shanxi Province, China

Publisher

Elsevier BV

Subject

Applied Mathematics,Electrical and Electronic Engineering,Computer Science Applications,Control and Systems Engineering

Reference46 articles.

1. Prediction of NOX emission from coal fired power plant based on real-time model updates and output bias update;Ahmed;Journal of Chemical Engineering of Japan,2015

2. Multi-level hybrid support vector machine and extreme learning machine based on modified K-means for intrusion detection system;Al-Yaseen;Expert Systems with Applications,2017

3. Multi-variable measurements and optimization of GMAW parameters for API-X42 steel alloy using a hybrid BPNN–PSO approach;Azadi Moghaddam;Measurement,2016

4. Prediction of unburned carbon and NOX in a tangentially fired power station using single coals and blends;Backreedy;Fuel,2005

5. Numerical prediction of processes for clean and efficient combustion of pulverized coal in power plants;Belošević;Applied Thermal Engineering,2015

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1. Prediction of NOx Emissions in Thermal Power Plants Using a Dynamic Soft Sensor Based on Random Forest and Just-in-Time Learning Methods;Sensors;2024-07-09

2. A physics-informed neural network that considers monotonic relationships for predicting NO emissions from coal-fired boilers;Fuel;2024-05

3. A study on nitrogen oxide emission prediction in Taichung thermal power plant using artificial intelligence (AI) model;International Journal of Hydrogen Energy;2024-04

4. Dynamic NOX emission concentration prediction based on the combined feature selection algorithm and deep neural network;Energy;2024-04

5. An Interpretable Time Series Forecasting Model for Predicting NOx Emission Concentration in Ferroalloy Electric Arc Furnace Plants;Mathematics;2024-03-16

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