In order to evaluate the level of the coal mine essential safety management, the comprehensive index system was designed base on the connotation principle of the mine essential safety management. Due to the disadvanta...In order to evaluate the level of the coal mine essential safety management, the comprehensive index system was designed base on the connotation principle of the mine essential safety management. Due to the disadvantage of index weight setting by subjective idea in the former method, support vector classification algorithm was used to assess the level of coal mine essential safety management. According to the advantages of the global search capability of the genetic algorithm, support vector classification parameters optimization method was proposed based on genetic algorithm, and genetic algorithm-support vector classification model of coal mine essential safety management assessment was established. Learning samples were constructed on the basis of former data of mine essential safety management evaluation. The test results show that the genetic algorithm-support vector classification model has higher evaluation accuracy and good generalization ability, and the advantage of no need for artificial setting of index weight and absence of the subjective factors influence to evaluation results.展开更多
基金Supported by the National Nature Science Foundation of China （51174082） the Doctoral Research Fund of Henan Polytechnic University （B2010-69 B2011-056） the Guidance Program for Science and Technology Research of China National Coal Association （MTKJ2010-383）
文摘In order to evaluate the level of the coal mine essential safety management, the comprehensive index system was designed base on the connotation principle of the mine essential safety management. Due to the disadvantage of index weight setting by subjective idea in the former method, support vector classification algorithm was used to assess the level of coal mine essential safety management. According to the advantages of the global search capability of the genetic algorithm, support vector classification parameters optimization method was proposed based on genetic algorithm, and genetic algorithm-support vector classification model of coal mine essential safety management assessment was established. Learning samples were constructed on the basis of former data of mine essential safety management evaluation. The test results show that the genetic algorithm-support vector classification model has higher evaluation accuracy and good generalization ability, and the advantage of no need for artificial setting of index weight and absence of the subjective factors influence to evaluation results.
