基于语义的决策模型能力评估与选择方法  

Semantics based decision model capacity evaluation and selection

作　　者：张波[1] 向阳[1] 

机构地区：[1]同济大学电子与信息工程学院,上海201804

出　　处：《控制与决策》2010年第9期1324-1328,1332,共6页Control and Decision

基　　金：国家自然科学基金项目(70771077);国家自然科学基金青年基金项目(60903032);国家863计划项目(2008AA04Z106);上海市科委制造业信息化专项基金项目(08DZ1122300);上海信息化发展专项基金项目(200901015)

摘　　要：本体决策模型选择的最佳手段是使计算机在理解决策问题和决策模型自身能力的基础上进行.通过领域本体,决策问题和决策模型可以具备被计算机自动理解的形式化语义.在理解决策问题语义的基础上,系统可选择对应的求解模型类别并获取决策问题内在需求,进而根据对应的候选模型语义对其具备的能力进行评估,选择最适合于决策问题的决策模型.最后,实例分析结果表明了这种模型选择方法是有效且可行的.The best method of decision model selection is based on fully understanding the meanings of decision problem and the capacities of decision model. Through domain ontology, decision problem and decision model are described in form of formal semantics which can be understood automatically by computer. Due to the understanding semantics of decision problem, DSS can extract the requirement of problem and select the corresponding model class which can solve the problem. Then, the capacities of candidate models are evaluated according to the semantics of decision models and eventually find out decision model which is the most completive one for the problem. Finally, the example analyzing and experiment show that the model selection method is effective and feasible.

关 键 词：决策模型 语义 本体 能力评估 模型选择 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]