Application Of Logical Regression Based Hybrid Learning In Coal And Gas Outburst

Today,with the deepening of coal mine operation,the mining environment is becoming more dangerous and complex,and the safety problems of coal mines are particularly prominent.Once the coal and gas outburst accident becomes the primary problem that fetters the growth and growth of coal mining industry,it is urgent to solve.Based on the principle of logistic regression,this paper proposes the hybrid intelligent learning of logistic regression and convolutional network and the hybrid intelligent learning of logistic regression and Ada Boost.A coal type image recognition model based on logistic regression and convolutional network was designed in order to obtain the index information of coal type in real time.Based on the coal type image recognition model mixed with logistic regression and convolutional network,the convolutional network is used to extract the features of coal images first,then feature screening based on maximum pooling and feature dimensionality reduction based on principal component analysis are carried out,and finally,the features after dimensionality reduction are used to recognize the logistic regression.In order to efficiently predict the risk degree of gas outburst,a coal and gas outburst prediction model was designed based on the mixture of logistic regression and Ada Boost.Under the framework of Ada Boost,several logistic regression One-VS-Rest weak classifiers were connected to form a strong classifier.Then,considering gas pressure,coal type,geological structure,Protodyakonov coefficient,mining depth and initial release velocity,a coal and gas outburst prediction model based on logistic regression and Ada Boost mixture is constructed.In this paper,using Python language as a tool,using Tensor Flow library,Scikit-Learn library,Open CV library and other machine learning and image processing libraries,to implement the construction of coal image recognition model based on logistic regression and convolutional network,and the prediction model of coal and gas outburst based on logistic regression and Ada Boost.Using the field data,the experiment was carried out.The experimental results show that the model can quickly obtain high accuracy results,and the modeling time is short and stable.There are 41 figures,9 tables and 55 references in this paper.