空区探测方法优选的ANP模型及其应用

目前矿山空区探测方法众多,但缺乏对其进行优化选择的分析模型。为了提高特定条件下空区探测方法选择的科学性、合理性,采用网络分析法(ANP)将决策问题分解成控制层和网络层。就这些层中的元素而言,用一种标度对人的主观判断进行客观量化后,对其实施定性、定量分析。综合考虑空区探测方法的技术、经济、人机设计及环境指标,构建空区探测方法综合评价体系,确定各判断准则间的相互影响关系,建立空区探测方法优选决策问题的ANP结构,借助Super Deci-sions软件计算参选方法基于各影响因素的综合优先权,从而确定适用于特定条件下的空区探测方法。结果表明,该模型能够随着工作环境的改变而计算影响因素优先权,使空区探测方法根据工作环境的改变而调整。

An ANP-based Analytical Model for Selecting the Best Cavity Probing Method and Its Application

For the numerous methods of cavity detection and lacking of corresponding selective analytical model,in order to choose the scientific and reasonable cavity detection method under different situations,the ANP decision issue was broken into two layers,the control layer and network layer,using.For the elements in the layers,a certain yardstick was objectively applied to quantify subjective evaluations by individuals,upon which qualitative and quantitative analyses of them were conducted then.This paper took into consideration the technical,economical and ergonomic indexes concerning the cavity probing methods.An overall cavity probing method evaluation system was established to decide the mutually influential relations among the decision rules,which contributed to the building of ANP network architecture for the selection of optimal cavity probing method.Considering all the relevant elements,Super Decisions software packet was used to calculate the overall precedence for all the methods available,based on which best cavity probing method in light of a specific situation could be decided.By building the model,result shows that the synthetic superior degrees can be recounted according to change in work environment,and it makes cavity detection method more scientific and flexible to adjust to the change in work environment.