Ignition temperature and activation energy of power coal blends predicted with back-propagation neural network models-Reference-Cited by-同舟云学术

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Ignition temperature and activation energy of power coal blends predicted with back-propagation neural network models

Published:2016-06 Issue: Volume:173 Page:230-238
ISSN:0016-2361
Container-title:Fuel
language:en
Short-container-title:Fuel

Author:

Cheng Jun,Wang Xin,Si Tingting,Zhou Fan,Zhou Junhu,Cen Kefa

Funder

National Natural Science Foundation

National Basic Research Program

Publisher

Elsevier BV

Subject

Organic Chemistry,Energy Engineering and Power Technology,Fuel Technology,General Chemical Engineering

Reference20 articles.

1. The effect of the coal blending method in a coal fired boiler on carbon in ash and NOx emission;Baek;Fuel,2014

2. An experimental study of the effect of coal blending on ash deposition;Rushdi;Fuel,2004

3. Effects of coal blending on the reduction of PM10 during high-temperature combustion 1. Mineral transformations;Wang;Fuel,2008

4. Predicting coal ash fusion temperature with a backpropagation neural network model;Yin;Fuel,1998

5. Development of an artificial neural network model for the steam process of a coal biomass cofired combined heat and power (CHP) plant in Sweden;De;Energy,2007

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