The Consistency Research Of The Human Factors Analysis Results Of Mining Accidents Based On Group Decision

Mining is the highest risk industry division in China for a long time, and the human factors are always identified as the primary factor for the mine accidents. Furthermore, since the human factors analysis and classification system(HFACS) is proposed from the field of aviation, consequently, the factors contained in HFACS are difficult to correspond with the mining accidents, which always obtain inconsistency results when different analysts use HFACS to analysis the same mining accident. How to improve the accuracy of the human factor analysis results is important to achieve the effectively use of "big data" in mining accidents. Therefore, it is significant to reduce the incidence of the human factors analysis results of mining accidents.In order to improve the accuracy of the human factors analysis results, the human factors analysis and classification systems is sometimes used by several analysts to analysis the contribute factors for mining accidents. Consequently, aggregated method for the analysis results is proposed based on group decision theory in this work. For different forms of human factors analysis results, based on the consistency analysis of group human factors analysis results, analysts' weights are determined by difference of these results. And then, every human factor's group consistency analysis results in a mining accident are obtained by weighting aggregation to improve the objectivity of the human factors analysis results. Furthermore, an example is used to verify the effectiveness of the proposed method, and laid a foundation to improve the scientific and accurate data for mining safety database.