基于粗糙集与未确知测度理论的突出危险性评价模型

建立了基于粗糙集和未确知测度理论的突出危险性评价模型,应用粗糙集理论对多种突出危险性预测指标的现场实测数据进行分析,并删减相对不重要的指标,从而达到指标优选的目的,根据各指标的相对重要程度进行权重分配;应用未确知测度理论构建预测指标的未确知函数,并计算未确知综合评价向量,依照置信度识别准则进行等级判定,最终得出突出危险性评价结果。为验证模型的实用性和有效性,对该模型进行了应用,并与模糊预测方法、回归预测方法的结果进行对比。研究结果表明,该模型的评价效果较好,更加符合现场的实际情况。

Outburst Risk Evaluation Model Based on Rough Set and Unascertained Measure Theory

outburst risk evaluationa model based on rough set theory and unascertained measure theory was established.For the aim of selecting the optimistic indexes,the paper analyzed the field datum of a variety of outburst risk predictors based on rough set theory,and deleted the unimportant indexes.The weight were distributed based on the relative importance of each indicator.The unascertained function of predictor was established based on the unascertained theory and the unascertained comprehensive evaluation vector was calculated.The outburst risk evaluation results was obtained eventually based on the classification of confidence recognition criteria.The model was applied to verify its practicality and effectiveness.Comparing with the results of fuzzy forecasting method and regression prediction method,the results showed that the evaluating effect of the model was better,and more in line with the actual situation of the scene.