This paper discusses the application of the model in predicting for hydrothermal Cu, Ag, Au and Pb-Zn occurrences in northwestern Yunnan. Geochemical, lineament and lithology data were the selected recognition criteri...This paper discusses the application of the model in predicting for hydrothermal Cu, Ag, Au and Pb-Zn occurrences in northwestern Yunnan. Geochemical, lineament and lithology data were the selected recognition criteria. The mentioned criteria varied against 75 known hydrothermal occurrences; the geochemical data had a weight of (W^+= 1. 209 7, W^- =-0. 748 1) being the maximum among the three and the rest lineament and lithology have (W^+= 0.7424, W^-= -0.449 6), (W^+= 0.378 7,W^-=-0.6243) respectively. The application was successful since the predicted results covers about 70% of the known deposits and predicted unknown areas.展开更多
为了实现复杂战场环境下空中目标敌我属性的综合识别,在利用证据权重衡量信息可信度的基础上,提出了一种基于DS证据理论和直觉模糊集相结合(Dempster-Shafer evidence theory-intuitionistic fuzzy sets,DST-IFS)的综合敌我识别方法。首...为了实现复杂战场环境下空中目标敌我属性的综合识别,在利用证据权重衡量信息可信度的基础上,提出了一种基于DS证据理论和直觉模糊集相结合(Dempster-Shafer evidence theory-intuitionistic fuzzy sets,DST-IFS)的综合敌我识别方法。首先,分析了空中目标综合敌我识别问题,给出了具体的识别流程;然后,针对DS(DempsterShafer)函数向直觉模糊集转化过程中存在增大信息不确定性的问题,提出了一种信度分配方法用于直觉模糊隶属度和非隶属度赋值,并利用算例验证了信度分配方法的适应性和有效性;接着,给出了基于理想点法(technique for order preference by similarity to ideal solution,TOPSIS)的DST-IFS决策方法步骤;在此基础上,提出了一种基于DST-IFS的空中目标综合敌我识别的方法;最后进行了实例分析,验证了该综合敌我识别方法的有效性。展开更多
文摘This paper discusses the application of the model in predicting for hydrothermal Cu, Ag, Au and Pb-Zn occurrences in northwestern Yunnan. Geochemical, lineament and lithology data were the selected recognition criteria. The mentioned criteria varied against 75 known hydrothermal occurrences; the geochemical data had a weight of (W^+= 1. 209 7, W^- =-0. 748 1) being the maximum among the three and the rest lineament and lithology have (W^+= 0.7424, W^-= -0.449 6), (W^+= 0.378 7,W^-=-0.6243) respectively. The application was successful since the predicted results covers about 70% of the known deposits and predicted unknown areas.
文摘为了实现复杂战场环境下空中目标敌我属性的综合识别,在利用证据权重衡量信息可信度的基础上,提出了一种基于DS证据理论和直觉模糊集相结合(Dempster-Shafer evidence theory-intuitionistic fuzzy sets,DST-IFS)的综合敌我识别方法。首先,分析了空中目标综合敌我识别问题,给出了具体的识别流程;然后,针对DS(DempsterShafer)函数向直觉模糊集转化过程中存在增大信息不确定性的问题,提出了一种信度分配方法用于直觉模糊隶属度和非隶属度赋值,并利用算例验证了信度分配方法的适应性和有效性;接着,给出了基于理想点法(technique for order preference by similarity to ideal solution,TOPSIS)的DST-IFS决策方法步骤;在此基础上,提出了一种基于DST-IFS的空中目标综合敌我识别的方法;最后进行了实例分析,验证了该综合敌我识别方法的有效性。