Research On The Feature Selection And Its Application In The Data Processing Of The Mineral Measuring And Monitoring System

According to the thought of "theory research, experiment data validate, actual data application, conclusion and analysis", and new technology of feature selection, the acquired data which reflects the safety state in coal mine is processed, and that improve the safety state of coal mine in China because it provides credible data for safety prediction.Genetic Algorithm (GA) is applied to select the characteristic data, and the realization of GA is based on the functions provided by MATLAB GA tools. The following show the primary methods and conclusions in this paper.Firstly, the data is separated to subsections according to the number of the characteristic data needed. Using GA in subsections and then we can adopt the results as the characteristic data of subsections. This has taken full advantage of global searching and optimization performances of GA.Secondly, both the experiment data and actual data are used to validate the algorithm. According the experiment data acquired from sine wave with white noise, the binary code method and floating-point code method are used to validate the feasibility of algorithm. Considering the characteristics of actual data such as great capacity, wide value scope and high precious, the follow method is applied to improve the performance of GA. After pre-processing of original data and floating-point coding, the value scope of initial population can be obtained by adding or reducing the original data in subsections.At last, both the validating results of experiment data and actual data indicate that: firstly, the characteristic data obtained by the feature selection algorithm represent the original data sufficiently, and that satisfy the desire of paper; secondly, the extraction rate changes following the termination generation. Furthermore, the algorithm can be used in other monitoring systems to acquire data feature.