Prediction of coal spontaneous combustion temperature based on improved grey wolf optimizer algorithm and support vector regression-Reference-Cited by-同舟云学术

Prediction of coal spontaneous combustion temperature based on improved grey wolf optimizer algorithm and support vector regression

Published:2022-09 Issue: Volume:324 Page:124670
ISSN:0016-2361
Container-title:Fuel
language:en
Short-container-title:Fuel

Author:

Li Shuang,Xu Kun,Xue Guangzhe,Liu Jiao,Xu Zhengquan

Publisher

Elsevier BV

Subject

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

Reference30 articles.

1. Risk evaluation of coal spontaneous combustion on the basis of auto-ignition temperature;Zhang;Fuel,2018

2. Study on the coupling evolution of air and temperature field in coal mine goafs based on the similarity simulation experiments;Zheng;Fuel,2021

3. An novel experimental study on the thermorunaway behavior and kinetic characteristics of oxidation coal in a low temperature reoxidation process;Lu;Fuel,2022

4. Prediction indices and limiting parameters of coal spontaneous combustion in the huainan mining area in china;Ma;Fuel,2020

5. Numerical simulation of coal dust self–ignition and combustion under inclination conditions;Shi;Energy,2022

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