数据驱动下图模型冲突分析决策支持系统构建研究OA北大核心CSTPCD

Nowadays,conflicts frequently occur due to issues such as economy,technology,geostrategy,and international order,and the scale of conflicts is shifting from individual and small-scale group conflicts to complex large-scale group conflicts.Compared to conflicts between individuals,large-scale group conflicts have a longer duration and wider scope,which have a negative impact on China's social order and economic development.Graph model for conflict resolution(GMCR)has been widely applied to water resources,environmental management and economic policy as a theoretical tool for solving conflict problems,and has achieved good results.However,the increasing number of participants and strategies in conflict have led to an exponential increase in situation,and the uncertainty of the subject's preference behavior is enhanced,so the traditional decision support system GMCRⅡ is difficult to solve such complex conflicts.Based on the algebraic expression of strength preference conflict analysis theory,this paper designs a conflict analysis WEB system SP-GMCRDSS based on.NET platform,including four modules:feasible state generation,state transition setting,strength preference sequence generation and stability analysis engine.Compared with existing systems,SP-GMCRDSS can more efficiently assist conflict analysts in solving large and complex data-driven conflicts.The text mining technology is used to extract strategy,which can assist analysts to determine the input of decision support system,and reduce the subjectivity of model building.Finally,modeling,solving,and analysis functions of the system are demonstrated through the case"Lanzhou Water Pollution Conflict Event".