Prediction of temperature and CO concentration fields based on BPNN in low-temperature coal oxidation-Reference-Cited by-同舟云学术

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Prediction of temperature and CO concentration fields based on BPNN in low-temperature coal oxidation

Published:2021-01 Issue: Volume:695 Page:178820
ISSN:0040-6031
Container-title:Thermochimica Acta
language:en
Short-container-title:Thermochimica Acta

Author:

Zhao Jianqiao,Yang Deguang,Wu Jiaxin,Meng Xianliang,Li Xiao,Wu Guoguang,Miao Zhenyong,Chu Ruizhi,Yu Shi

Funder

National Nature Science Foundation Funded Project of China

Major Science and Technology Project of Shanxi Province

Publisher

Elsevier BV

Subject

Physical and Theoretical Chemistry,Condensed Matter Physics,Instrumentation

Reference46 articles.

1. Structural differences of spontaneous combustion prone inertinite-rich chinese lignite coals: insights from XRD, solid-state C-13 NMR, LDIMS, and HRTEM;Zhang;Energy. Fuel.,2019

2. Lessons learned from fires of the wood caused by the spontaneous combustion of coal dust in underground mines;Shi;J. Therm. Anal. Calorim.,2017

3. Multifaceted processes controlling the distribution of hazardous compounds in the spontaneous combustion of coal and the effect of these compounds on human health;Oliveira;Environ. Res.,2018

4. Controlling factors of symbiotic disaster between coal gas and spontaneous combustion in longwall mining gobs;Xia;Fuel,2016

5. Multi-physics coupling model of coal spontaneous combustion in longwall gob area based on moving coordinates;Liu;Fuel,2017

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1. Analysis of stage parameters of low-temperature oxidation of water-soaked coal based on kinetic principles;Science of The Total Environment;2024-10

2. A sensorless centrifugal pump operation states estimation method based on HSSA-BPNN;Measurement;2024-09

3. Dynamic prediction of high-temperature points in longwall gobs under a multi-field coupling framework;Process Safety and Environmental Protection;2024-07

4. Research on Prediction and Early Warning Technology of Gob Spontaneous Combustion Based on RBF Neural Network;Combustion Science and Technology;2024-06-17

5. A spatio-temporal temperature prediction model for coal spontaneous combustion based on back propagation neural network;Energy;2024-05

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