This paper reports an aspiration-directed, model-based decision support system (AMDSS) integrated with a knowledge-based simulation system. The system is designed to study China's mid-range economic development st...This paper reports an aspiration-directed, model-based decision support system (AMDSS) integrated with a knowledge-based simulation system. The system is designed to study China's mid-range economic development strategy. The capacity of the system is enhanced by the knowledge-based component which provides a knowledge-based simulation environment for model management. Currently the system has passed the stage of prototype and achieves its implementation capacity. The paper first presents the mathematical aspects of decision making including aspiration-directed decision making, then discusses the architecture of the system. The purpose of the paper is to provide insights into how such an integrated system could provide decision support for complex decision analysis.展开更多
Ballistic missile defense system (BMDS) is important for its special role in ensuring national security and maintaining strategic balance. Research on modeling and simulation of the BMDS beforehand is essential as dev...Ballistic missile defense system (BMDS) is important for its special role in ensuring national security and maintaining strategic balance. Research on modeling and simulation of the BMDS beforehand is essential as developing a real one requires lots of manpower and resources. BMDS is a typical complex system for its nonlinear, adaptive and uncertainty characteristics. The agent-based modeling method is well suited for the complex system whose overall behaviors are determined by interactions among individual elements. A multi-agent decision support system (DSS), which includes missile agent, radar agent and command center agent, is established based on the studies of structure and function of BMDS. Considering the constraints brought by radar, intercept missile, offensive missile and commander, the objective function of DSS is established. In order to dynamically generate the optimal interception plan, the variable neighborhood negative selection particle swarm optimization (VNNSPSO) algorithm is proposed to support the decision making of DSS. The proposed algorithm is compared with the standard PSO, constriction factor PSO (CFPSO), inertia weight linear decrease PSO (LDPSO), variable neighborhood PSO (VNPSO) algorithm from the aspects of convergence rate, iteration number, average fitness value and standard deviation. The simulation results verify the efficiency of the proposed algorithm. The multi-agent DSS is developed through the Repast simulation platform and the constructed DSS can generate intercept plans automatically and support three-dimensional dynamic display of missile defense process.展开更多
This study aimed to develop a clinical Decision Support Model (DSM) which is software that provides physicians and other healthcare stakeholders with patient-specific assessments and recommendation in aiding clinical ...This study aimed to develop a clinical Decision Support Model (DSM) which is software that provides physicians and other healthcare stakeholders with patient-specific assessments and recommendation in aiding clinical decision-making while discharging Breast cancer patient since the diagnostics and discharge problem is often overwhelming for a clinician to process at the point of care or in urgent situations. The model incorporates Breast cancer patient-specific data that are well-structured having been attained from a prestudy’s administered questionnaires and current evidence-based guidelines. Obtained dataset of the prestudy’s questionnaires is processed via data mining techniques to generate an optimal clinical decision tree classifier model which serves physicians in enhancing their decision-making process while discharging a breast cancer patient on basic cognitive processes involved in medical thinking hence new, better-formed, and superior outcomes. The model also improves the quality of assessments by constructing predictive discharging models from code attributes enabling timely detection of deterioration in the quality of health of a breast cancer patient upon discharge. The outcome of implementing this study is a decision support model that bridges the gap occasioned by less informed clinical Breast cancer discharge that is based merely on experts’ opinions which is insufficiently reinforced for better treatment outcomes. The reinforced discharge decision for better treatment outcomes is through timely deployment of the decision support model to work hand in hand with the expertise in deriving an integrative discharge decision and has been an agreed strategy to eliminate the foreseeable deteriorating quality of health for a discharged breast cancer patients and surging rates of mortality blamed on mistrusted discharge decisions. In this paper, we will discuss breast cancer clinical knowledge, data mining techniques, the classifying model accuracy, and the Python web-based decision support model that predicts avoidable re-hospitalization of a breast cancer patient through an informed clinical discharging support model.展开更多
Many concrete real life problems ranging from economic and business to industrial and engineering may be cast into a multi-objective optimisation framework. The redundancy of existing methods for solving this kind of ...Many concrete real life problems ranging from economic and business to industrial and engineering may be cast into a multi-objective optimisation framework. The redundancy of existing methods for solving this kind of problems susceptible to inconsistencies, coupled with the necessity for checking inherent assumptions before using a given method, make it hard for a nonspecialist to choose a method that fits well the situation at hand. Moreover, using blindly a method as proponents of the hammer principle (when you only have a hammer, you want everything in your hand to be a nail) is an awkward approach at best and a caricatural one at worst. This brings challenges to the design of a tool able to help a Decision Maker faced with these kinds of problems. The help should be at two levels. First the tool should be able to choose an appropriate multi-objective programming technique and second it should single out a satisfying solution using the chosen technique. The choice of a method should be made according to the structure of the problem and to the Decision Maker’s judgment value. This paper is an attempt to satisfy that need. We present a Decision Aid Approach that embeds a sample of good multi-objective programming techniques. The system is able to assist the Decision Maker in the above mentioned two tasks.展开更多
针对航班地面保障过程决策能力不足、运行效率低下的问题,提出一种基于国防部体系结构框架(department of defense architecture framework,DoDAF)的航班地面保障过程决策支持模型。从保障作业、保障资源以及二者间关联关系出发,定量描...针对航班地面保障过程决策能力不足、运行效率低下的问题,提出一种基于国防部体系结构框架(department of defense architecture framework,DoDAF)的航班地面保障过程决策支持模型。从保障作业、保障资源以及二者间关联关系出发,定量描述航班地面保障过程,将DoDAF与基于模型的系统工程(model-based systems engineering,MBSE)相结合建立航班地面保障过程决策支持模型,建立决策效用函数,分析航班保障各环节综合保障的效用值。对比实际数据与本文决策支持模型得到的数据,结果表明决策后的撤轮挡时间与目标撤轮档时间的平均绝对误差对比实际撤轮档时间和目标撤轮档时间的平均绝对误差降低1.42 min,均方根误差降低0.95 min,对于不同机型航班,决策后的保障服务时间与计划保障时间相对误差对比决策前分别降低31%、17%和42%,同时可以得到保障时间与保障效用的关系,证明本文提出的决策模型的可行性和有效性。展开更多
保障系统结构建模是发展和构建新一代航空装备智能保障系统的重要基础。航空装备保障系统涉及保障要素多、交联关系复杂,需从系统工程的角度开展顶层设计,并采用统一的结构框架对其体系结构进行建模表征。引入美国国防部架构框架(Depart...保障系统结构建模是发展和构建新一代航空装备智能保障系统的重要基础。航空装备保障系统涉及保障要素多、交联关系复杂,需从系统工程的角度开展顶层设计,并采用统一的结构框架对其体系结构进行建模表征。引入美国国防部架构框架(Departmeant of Defense Architecture Framework,DoDAF)体系结构框架,提出基于“概念-任务-能力”的体系结构开发序列,构建航空装备智能保障系统的能力、保障活动、各保障要素的信息交互及组织关系等视图模型,得到“能力层-需求层-技术层”之间的对应关系。该方法能够全面地描述航空装备智能保障系统体系结构,提高不同保障要素之间的互操作性,并将其转化为具体的设计要求,可为航空装备智能保障系统开发提供支持。展开更多
文摘This paper reports an aspiration-directed, model-based decision support system (AMDSS) integrated with a knowledge-based simulation system. The system is designed to study China's mid-range economic development strategy. The capacity of the system is enhanced by the knowledge-based component which provides a knowledge-based simulation environment for model management. Currently the system has passed the stage of prototype and achieves its implementation capacity. The paper first presents the mathematical aspects of decision making including aspiration-directed decision making, then discusses the architecture of the system. The purpose of the paper is to provide insights into how such an integrated system could provide decision support for complex decision analysis.
文摘Ballistic missile defense system (BMDS) is important for its special role in ensuring national security and maintaining strategic balance. Research on modeling and simulation of the BMDS beforehand is essential as developing a real one requires lots of manpower and resources. BMDS is a typical complex system for its nonlinear, adaptive and uncertainty characteristics. The agent-based modeling method is well suited for the complex system whose overall behaviors are determined by interactions among individual elements. A multi-agent decision support system (DSS), which includes missile agent, radar agent and command center agent, is established based on the studies of structure and function of BMDS. Considering the constraints brought by radar, intercept missile, offensive missile and commander, the objective function of DSS is established. In order to dynamically generate the optimal interception plan, the variable neighborhood negative selection particle swarm optimization (VNNSPSO) algorithm is proposed to support the decision making of DSS. The proposed algorithm is compared with the standard PSO, constriction factor PSO (CFPSO), inertia weight linear decrease PSO (LDPSO), variable neighborhood PSO (VNPSO) algorithm from the aspects of convergence rate, iteration number, average fitness value and standard deviation. The simulation results verify the efficiency of the proposed algorithm. The multi-agent DSS is developed through the Repast simulation platform and the constructed DSS can generate intercept plans automatically and support three-dimensional dynamic display of missile defense process.
文摘This study aimed to develop a clinical Decision Support Model (DSM) which is software that provides physicians and other healthcare stakeholders with patient-specific assessments and recommendation in aiding clinical decision-making while discharging Breast cancer patient since the diagnostics and discharge problem is often overwhelming for a clinician to process at the point of care or in urgent situations. The model incorporates Breast cancer patient-specific data that are well-structured having been attained from a prestudy’s administered questionnaires and current evidence-based guidelines. Obtained dataset of the prestudy’s questionnaires is processed via data mining techniques to generate an optimal clinical decision tree classifier model which serves physicians in enhancing their decision-making process while discharging a breast cancer patient on basic cognitive processes involved in medical thinking hence new, better-formed, and superior outcomes. The model also improves the quality of assessments by constructing predictive discharging models from code attributes enabling timely detection of deterioration in the quality of health of a breast cancer patient upon discharge. The outcome of implementing this study is a decision support model that bridges the gap occasioned by less informed clinical Breast cancer discharge that is based merely on experts’ opinions which is insufficiently reinforced for better treatment outcomes. The reinforced discharge decision for better treatment outcomes is through timely deployment of the decision support model to work hand in hand with the expertise in deriving an integrative discharge decision and has been an agreed strategy to eliminate the foreseeable deteriorating quality of health for a discharged breast cancer patients and surging rates of mortality blamed on mistrusted discharge decisions. In this paper, we will discuss breast cancer clinical knowledge, data mining techniques, the classifying model accuracy, and the Python web-based decision support model that predicts avoidable re-hospitalization of a breast cancer patient through an informed clinical discharging support model.
文摘Many concrete real life problems ranging from economic and business to industrial and engineering may be cast into a multi-objective optimisation framework. The redundancy of existing methods for solving this kind of problems susceptible to inconsistencies, coupled with the necessity for checking inherent assumptions before using a given method, make it hard for a nonspecialist to choose a method that fits well the situation at hand. Moreover, using blindly a method as proponents of the hammer principle (when you only have a hammer, you want everything in your hand to be a nail) is an awkward approach at best and a caricatural one at worst. This brings challenges to the design of a tool able to help a Decision Maker faced with these kinds of problems. The help should be at two levels. First the tool should be able to choose an appropriate multi-objective programming technique and second it should single out a satisfying solution using the chosen technique. The choice of a method should be made according to the structure of the problem and to the Decision Maker’s judgment value. This paper is an attempt to satisfy that need. We present a Decision Aid Approach that embeds a sample of good multi-objective programming techniques. The system is able to assist the Decision Maker in the above mentioned two tasks.
文摘针对航班地面保障过程决策能力不足、运行效率低下的问题,提出一种基于国防部体系结构框架(department of defense architecture framework,DoDAF)的航班地面保障过程决策支持模型。从保障作业、保障资源以及二者间关联关系出发,定量描述航班地面保障过程,将DoDAF与基于模型的系统工程(model-based systems engineering,MBSE)相结合建立航班地面保障过程决策支持模型,建立决策效用函数,分析航班保障各环节综合保障的效用值。对比实际数据与本文决策支持模型得到的数据,结果表明决策后的撤轮挡时间与目标撤轮档时间的平均绝对误差对比实际撤轮档时间和目标撤轮档时间的平均绝对误差降低1.42 min,均方根误差降低0.95 min,对于不同机型航班,决策后的保障服务时间与计划保障时间相对误差对比决策前分别降低31%、17%和42%,同时可以得到保障时间与保障效用的关系,证明本文提出的决策模型的可行性和有效性。
文摘保障系统结构建模是发展和构建新一代航空装备智能保障系统的重要基础。航空装备保障系统涉及保障要素多、交联关系复杂,需从系统工程的角度开展顶层设计,并采用统一的结构框架对其体系结构进行建模表征。引入美国国防部架构框架(Departmeant of Defense Architecture Framework,DoDAF)体系结构框架,提出基于“概念-任务-能力”的体系结构开发序列,构建航空装备智能保障系统的能力、保障活动、各保障要素的信息交互及组织关系等视图模型,得到“能力层-需求层-技术层”之间的对应关系。该方法能够全面地描述航空装备智能保障系统体系结构,提高不同保障要素之间的互操作性,并将其转化为具体的设计要求,可为航空装备智能保障系统开发提供支持。
