Application Of KNN Algorithm In Identification Of Mine Water Source

Under the coal mine,the occurrence of water pollution is mine safety work in the focus of prevention and control of the object.Water inrush is the main manifestation of floods,in the event of serious physical and economic losses.Therefore,the work of prevention and control of water damage is very important.In the work of water pollution prevention and control,it is also indispensable for the identification of mine water source.For the traditional identification methods,such as water chemistry method,its short time and low efficiency are not solved well.In view of these situations,this paper presents the application of KNN algorithm combined with LIF technology in mine water source identification.Firstly,the origin of the underground water source is analyzed,and the reason of the mine and the underground layer of the mine water source are introduced in detail.The harm of the mine safety is analyzed.And then the water source of the mine water source made a request and introduced for the mine water sample extraction work is very difficult,and the extraction of water samples need to be pre-experimental treatment,to meet the requirements of the experiment.And then the experimental equipment used in the experiment were introduced,the experimental equipment is self-developed mining equipment,is currently in the laboratory stage.The equipment is used to collect the spectral data of the mine water source,and the equipment parameters are set to ensure that the acquisition process is carried out in the darlkroom,and then the acquired raw data of the spectrum is stored in the host computer and used.In the spectral data processing,it is necessary to carrry out spectral preprocessing,this paper uses a variety of pretreatment methods,play a comparative role in which to select the best spectral pretreatment method.This paper also introduces KNN algorithm and some improved KNN algorithm,and analyzes the principle of the improved algorithm.And the KNN algorithm is used to classify the spectral data at the same time.On the basis of changing the K value,the accuracy of the improved KNN algorithm is analyzed and the best KNN algorithm is selected.Experiments used in the software MATLAB and SPSS,the data processing has a great function,the operation is also very simple.Finally,the actual classification experiment is carried out on the mine water source collected from a mining area in Huainan.The improved KNN algorithm is used to classify the spectral data.The accuracy of the classification is very impressive,and then the KNN algorithm is proved in the mine water source identification The application is very feasible,and has a high value.For the application of KNN algorithm in mine water source,this kind of recognition classification method proposed in this paper is the first application.For its simulation results and the actual experimental analysis results,it is shown that,KNN algorithm in the application of mine water source identification is very worthy of study.Also fully demonstrated,LIF technology in this area of special,can quickly establish the model of unknown water samples to identify and classify.Which for the future coal mine industry safety work,played a milestone in progress.