施工方案智能决策支持系统的面向对象模型

本文应用面向对象技术分析建筑施工组织设计，建立了包括施工项目子模型和施工活动子模型的施工领域模型，并在此基础上建立了施工方案智能决策支持系统模型。同时以钢筋砼建筑的施工方案决策为例，提出了知识库中知识的面向对象表示与增长机制以及决策过程的实现方法。     

施工方案决策知识的面向对象表示及其应用

施工方案的决策因其涉及大量的知识需要大型知识库支持本文以高层钢筋混凝土结构的为例，针对施工方案决策知识的特点，提出了该知识的面向对象表示法，同时确立了知识库的组织机制，并提出了相应的知识更新及增长机制和推现机制。     

投资项目管理的知识支持系统

从系统工程角度分析投资项目管理，针对建设投资项目系统存在的不确定性，提出建立了一个对整个投资项目管理周期的市场环境和企业的生产经营信息进行存储管理的知识库，用来辅助企业做出各种决策。采用面向对象技术构造知识库开发模型，给出了相应的模型结构，建立了现实性校验流程图，知识支持系统自始至终优化管理建设投资项目，增强了决策信息的可靠性，使项目投资最优化。     

基于推理的作战方案评估系统研究

根据作战方案评估要素对评估系统的要求进行了系统功能需求分析,根据该分析设计了作战方案评估系统的总体架构,采用面向对象知识表示法构建了评估系统的知识库,设计了基于规则推理方法的系统推理机,并给出了解释子系统的解释机制。该系统能够利用军事专家的经验和军事决策规则对作战方案进行评估,降低了人的主观因素对评估结果的影响,同时提高了评估结论的可信度。     

面向对象知识库的设计

面向对象技术的成熟及其在知识库系统中的应用，赋予了知识库一些新的概念。我们就此进行了较为深入的研究，并对知识表达、推理等作了一些探讨，采用基于面向对象技术的原型－代理机制定义和设计了知识对象，实现了知识共享，并通过对象间的消息传递形成多个推理机场境，从而进行知识的推理。本课题初步实现了一个具有一定推理辅助决策能力的原型知识库系统。     

设计决策专家系统的研究与实现

设计决策是一类重要的决策问题,是专家系统技术用于设计领域的主要求解对象,本文以冲裁工艺设计专家系统作为设计决策专家系统的一个实例,讨论其主要特点及实现技术,包括面向对象的知识表示和推理机制。图形的自动识别处理与生成,模糊实现技术,包括面向对象的知识表示和推理机制,图形的自动识别处理与生成,模糊知识表示与模糊推理技术的灵活应用。等等。     

面向对象的专家系统及其在柔性制造系统调度决策中的应用

本文把面向对象的方法用于专家系统的设计。文中结合柔性制造系统调度决策系统的设计，讨论了面向对象的知识获取、面向对象的知识表示及面向对象的推理的实现。文中介绍了面向对象的专家系统的实现软件。给出了实验结果。     

面向对象的专家系统及其柔性制造系统调度决策中的应用

本文把而向对象的方法用于专家系统的设计。文中结合柔性制造系统调度决策系统的设计，讨论了面向对象的知识获取、面向对象的知识表示及面向对象的推理的实现。文中介绍了面向对象的专家系统的实现软件。给出了实验结果。     

面向对象的专家系统开发工具

本文对一个面向对象的专家系统开发工具ＯＯＥＳＴ的结构和特点作了概要论述。它将多种知识表示融合于知识对象之中，提供了一面向对象的推理机制，具有定性推与定量计算相结合的功能。文中着重讨论了面向对象的知识表示方法，可视化的知识获取工具，面向对象的推理机等方面的内容。     

用面向对象的方法实现层次分类模型

本文首先简要地介绍了层次分类方法及其意义，以及建立分类模型的方法原则；然后，介绍了面向对象的思想，特别是面向对象的知识表达方法，并提出了用对象分类的结构来表达层次分类结构的方法；最后提出了面向对象的层次分类模型的求解机制——推理机制和解释机制，进而较全面、系统地提出了一种用崭新的面向对象的方法实现层次分类模型的方法技术。     

基于二元语义多属性决策方法的购房评估研究

提出了一种基于二元语义的购房评估方法。在经过调查分析基础上,构建了购房评估模型,将二元语义多属性决策方法应用于购房评估中,为购房者提供参考决策。最后通过实例说明了该方法运用于购房评估的具体过程,并验证了其合理性和可操作性。     

计算机生成航空兵力系统的专家知识表达方法

在计算机生成航空兵力系统中,采用了面向对象技术来表示专家知识,将专家知识封装在飞机对象的实体模型中,文中着重从决策角度叙述文中采用的专家知识表示方法的特点。其中,层次化的知识表示方法便于充分描述专家思想,也利于快速推理。另外文中采用了规则集逻辑有效性检测策略,在保证规则集充分性、唯一性基础上,使得规则集具有表示简单,推理快速的特点,最后给出系统实际运行结论。     

A knowledge-based decision support system for measuring the performance of government real estate investment

This paper describes a knowledge-based decision support system for measuring the performance of government real estate investment using DEA models. We propose an evaluation framework for real estate investment, including a database, a model base, and a knowledge base, to create a tool that a government can use to deal with decision-making problems via the Internet. This decision support system converts numerical data into information that can be used to evaluate possible real estate investments. Particularly, rules in the rule base are explained in more detail for illustrating the process of reasoning and KDSSGREI adapts quickly and accurately to infer and generate suggestions or actions. Data envelopment analysis (DEA) is used to perform efficiency analysis in this paper. Finally, we apply China's case to obtain strategies for reforming real estate investment.     

A knowledge-based decision support system for measuring the performance of government real estate investment

This paper describes a knowledge-based decision support system for measuring the performance of government real estate investment using DEA models. We propose an evaluation framework for real estate investment, including a database, a model base, and a knowledge base, to create a tool that a government can use to deal with decision-making problems via the Internet. This decision support system converts numerical data into information that can be used to evaluate possible real estate investments. Particularly, rules in the rule base are explained in more detail for illustrating the process of reasoning and KDSSGREI adapts quickly and accurately to infer and generate suggestions or actions. Data envelopment analysis (DEA) is used to perform efficiency analysis in this paper. Finally, we apply China's case to obtain strategies for reforming real estate investment.     

用于复杂系统建模与仿真的面向智能体技术

在构造兼具数据处理和知识处理能力的新型面对象型形式化体系上,根据复杂系统仿真的需要,使系统组分“对象”具有自主决策、控制和通信功能,建成多Agent系统。给出多Agent系统实现群组决策的示例。     

Basic algorithmic shell of onboard real-time advisory expert systems for operation situations typical for an object

The basic algorithmic shell for onboard real-time advisory expert systems for typical operation situations of anthropocentral objects is oriented on the formal model of the subject domain which includes the following ideas: general operation problems of an anthropocentral object, semantic networks of typical operation situations and problem subsituations in them. This system possesses two hierarchical levels in the knowledge base. On the first level, the production rules activate an adequate problem subsituation in real time. On the second level, problems of this subsituation are solved using the dynamic models of development of its fragments using the following inference mechanisms: multicriteria choice of a decision alternative, decision according to a precedent, decision based on an optimization problem, production rules. Upon development of an onboard real-time advisory expert system for a particular typical situation, the basic shell is filled with knowledge related to this typical situation with simultaneous rejection of unclaimed fragments. Upon program implementation of the algorithmic shell filled with knowledge, the shell is adapted to the onboard information environment of a given type of anthropocentral object and computational capabilities of the onboard computer system.     

面向对象的思想方法在决策支持系统中建立模型库的应用

本文介绍了面向对象程序设计的基本概念，思想和方法；     

Decision-making with uncertain data: Bayesian linear programming approach

This paper deals with decision making in a real time optimization context under uncertain data by linking Bayesian networks (BN) techniques (for uncertainties modeling) and linear programming (LP, for optimization scheme) into a single framework. It is supposed that some external events sensed in real time are susceptible to give relevant information about data. BN consists in graphical representation of probabilistic relationship between variables of a knowledge system and so permit to take into account uncertainty in an expert system by bringing together the classical artificial intelligence (AI) approach and statistics approach. They will be used to estimate numerical values of parameters subjected to the influence of random events for a linear programming program that perform optimization process in order to select optimal values of decision variables of a certain real time decision-making system.     

An active intelligent decision support system — Architecture and simulation

Development and implementation of decision support systems to support intelligent decision making is an area of research that has gained in importance in recent years. Due to the increased complexity of decision making, active involvement of the user and the computer in an intelligent way is necessary in the decision process. This paper presents issues in the design of an active intelligent decision support system (IDSS), develops an architectural model based on cooperative distributed problem solving, and performs a simulation of the system using object oriented programming for an example application in airfleet control.     

Conceptual modeling of causal map: Object oriented causal map

This study has been started from question “Is there a methodology that can make causal map comprised of causality as a database by using conceptual modeling method?” In this research, causal map is proposed to represent causal relation by using conceptual modeling method. Therefore, we formalize causality as a cognitive rule to allow us to control changes in the decision making environment. Such causality is embedded in the real world (application domain). And, user (decision maker) use to represent set of causality which decision-makers have retrieved from the set of knowledge or experiences in application domain. Such set of causality that decision-makers possess in their know–how and short (long) term memory are usually formalized by causal map. It is verified for users whether this causal map is helpful in solving their problems. By extending the basis of conceptual modeling theory (ontology theory, classification theory, decomposition theory, and semantic network theory), we introduce a concept of causal entity diagram and address why causal map is needed to analyze a specific domain knowledge for given decision problem solving. Finally, object oriented causal map (O2CM) were employed to verify usefulness of causal map for user (decision maker) in this study.