Optimized neural network to predict the experimental minimum period of coal spontaneous combustion

2022 ◽  
Author(s):  
Yang Xiao ◽  
Yong Cao ◽  
Kai-Qi Zhong ◽  
Lan Yin ◽  
Jun Deng
Keyword(s):  
Neural Network ◽  
Spontaneous Combustion ◽  
Coal Spontaneous Combustion ◽  
Minimum Period

Studied on Indicator Gases of Coal Based on BP Neural Network Forecasting System

2014 ◽  
Vol 685 ◽  
pp. 259-262 ◽  
Author(s):  
Bing Bian ◽  
Zhi Jian Liu ◽  
Wei Zhang
Keyword(s):  
Neural Network ◽  
Coal Mine ◽  
Bp Neural Network ◽  
Spontaneous Combustion ◽  
Coal Spontaneous Combustion ◽  
The Neural Network ◽  
Forecasting System

In order to forecast coal spontaneous combustion, take advantage of BP neural network. The date is recorded from one coal mine of Donghuantuo. The input of the neural network is the concentration of CO, CO2 and CH4 in different temperature and use CH4-to-CO, O2-to-CO2 ratio. In this way, the influence of the wind will be little. After trained, the network can show 0 or 1 which represent fire or not. After trained 43 times, the error is lower than 0.000 1. It proves that BP neural network can deal with the date of coal mine. What’s more, BP neural network has huge advantages.

Assessment of Self-Heating Susceptibility of Indian Coal Seams – A Neural Network Approach

2014 ◽  
Vol 59 (4) ◽  
pp. 1061-1076 ◽  
Author(s):  
D.C. Panigrahi ◽  
S.K. Ray
Keyword(s):  
Neural Network ◽  
Spontaneous Combustion ◽  
Potential Method ◽  
Oxidation Potential ◽  
Wet Oxidation ◽  
Experimental Conditions ◽  
Neural Network Approach ◽  
Indian Coal ◽  
Petrographic Analyses ◽  
Artificial Neural Network Ann

Abstract The paper addresses an electro-chemical method called wet oxidation potential technique for determining the susceptibility of coal to spontaneous combustion. Altogether 78 coal samples collected from thirteen different mining companies spreading over most of the Indian Coalfields have been used for this experimental investigation and 936 experiments have been carried out by varying different experimental conditions to standardize this method for wider application. Thus for a particular sample 12 experiments of wet oxidation potential method were carried out. The results of wet oxidation potential (WOP) method have been correlated with the intrinsic properties of coal by carrying out proximate, ultimate and petrographic analyses of the coal samples. Correlation studies have been carried out with Design Expert 7.0.0 software. Further, artificial neural network (ANN) analysis was performed to ensure best combination of experimental conditions to be used for obtaining optimum results in this method. All the above mentioned analysis clearly spelt out that the experimental conditions should be 0.2 N KMnO4 solution with 1 N KOH at 45°C to achieve optimum results for finding out the susceptibility of coal to spontaneous combustion. The results have been validated with Crossing Point Temperature (CPT) data which is widely used in Indian mining scenario.

Investigation on the suppression characteristic of deoxidization gel foam on coal spontaneous combustion

2021 ◽  
Author(s):  
Xin‐xiao Lu ◽  
Xue Xue ◽  
Cheng‐yan Wang ◽  
Guo‐yu Shi ◽  
Yun Xing ◽  
...  
Keyword(s):  
Spontaneous Combustion ◽  
Coal Spontaneous Combustion

scholarly journals Are Ionic Liquids Suitable for Suppressing Coal Spontaneous Combustion?

ACS Omega ◽  
2021 ◽  
Vol 6 (10) ◽  
pp. 6681-6690
Author(s):  
Xuanxuan Huang ◽  
Yongliang Xu ◽  
Yan Wang ◽  
Yao Li ◽  
Lanyun Wang ◽  
...  
Keyword(s):  
Ionic Liquids ◽  
Spontaneous Combustion ◽  
Coal Spontaneous Combustion
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