Study on condition analysis and temperature prediction of coal spontaneous combustion based on improved genetic algorithm

For major coal mine spontaneous combustion caused by disasters every year, various scholars have studied and analyzed the conditions of predicted temperature. Coal is an inevitable disaster, but studying surface covering to damp can greatly reduce occurrence combustion. We oxygen absorption in pores tendency its own water content for coal. The model experiment was carried out, correlation between different gas concentrations temperature produced during mixed samples analyzed. mines with contents levels, four times, performance evaluation comparison correct prediction under algorithm models were out. Finally, contrast experiment, curve fitting function minimum error value further compared, it be seen that combined genetic neural network has more accurate accuracy than single model. Through analysis phenomenon study anti-coal devices oxidation process, we reduced risk mining areas.