投资中基于模糊评价的群决策支持系统研究

专家评估是进行投资决策的手段之一,但由于多采用模糊评价,很难形成规范的系统来实现这一决策过程。而决策过程中产生的大量数据,以人力来计算既无法保证其正确性,又相当费时。因此,提出建立基于模糊评价的群决策支持系统,将采用模糊数学的方法、一致性分析以及主成分分析来构建一个计算机辅助决策系统来实现这个决策过程。结果表明,设计的系统能够迅速并准确帮助决策者进行决策分析,对决策者的决策提供有力的支持。     

基于知识发现的实用智能系统总体结构模型

知识发现系统与实用智能系统的有机融合成为信息管理、辅助决策支持、智能预测支持等领域亟待解决的关键问题之一。该文将以系统的观点和方法，从哲学方法论的角度来审视和研究基于知识发现的实用智能系统(如专家系统、决策支持系统和预测系统)的总体结构模型，并在此基础上为形成统一的、完备的和具有认知自主性的实用智能系统提供指导依据。     

大数据量推理专家系统外壳的研究与设计

CLIPS是现今主流的专家系统开发工具,但它不能直接访问外部数据库,而传统数据库又缺乏知识。本文提出将CLIPS与数据库系统Postgres结合,使用知识开发技术来降低存储在CLIPS主存储器内数据量。在此结构中,数据存储于Postgres,两系统的接口负责知识归纳,继而将知识传送到CLIPS的工作存储器进行推理。增加了CLIPS的大数据量推理能力。     

陆军合同作战指挥决策过程建模

现代作战的快速性,使得指挥员完成决策任务必须依赖于计算机辅助决策的帮助,而开发实用的决策支持系统需要有决策过程模型作为基础.针对目前这类过程模型存在的不足,根据陆军合同作战指挥的特点,通过将决策者和辅助决策者以及计算机应用程序功能综合纳入建模过程,提出了"一条主线、两层分级、三种关系,四种活动"为要素的主从式建模方法,其特点是便于决策者、辅助决策者以及参与决策者等相关人员的相互了解和沟通,突出了计算机应用程序在模型中应具有的基本功能,在辅助决策系统的分析设计上,为军事和技术人员提供了一种便于交互和便于理解的表示方式.     

基于DDS的模型驱动研究

目前模型已经可以部分参与生产环节,但还无法在大规模软件开发中直接使用模型,对象分析和设计模型还是主要用作软件系统的文档。软件分析师和设计师构建的模型仅仅作为程序员编写参考材料的辅助工具,而不能跟软件直接挂钩。为了解决这些软件生产过程中的非自动化和非标准化问题,OMG组织发布了模型驱动架构。通过对MDA标准的实现,软件模型可以直接被MDA工具翻译和执行,从而实现软件生产从人工到工业化的飞跃。决策支持系统是辅助决策者通过数据、模型和知识,以人机交互方式进行半结构化或非结构化决策的计算机应用系统。它是管理信息系统向更高一级发展而产生的先进信息管理系统。它为决策者提供分析问题、建立模型、模拟决策过程和方案的环境,调用各种信息资源和分析工具,帮助决策者提高决策水平和质量。     

遗传算法在决策支持系统和数据挖掘中的应用

决策支持系统和数据挖掘技术的应用已深入到企业管理、金融、办公及日常生活等各个领域。使用原先决策支持系统中的传统方法已远远不能满足决策者的需要,从而出现许多新技术新方法来辅助和完善决策支持过程。文中在介绍遗传算法的基础上,提出了一种将遗传算法与决策支持系统相结合的观点,阐述了基于遗传算法的决策支持系统的模型设计,且深入讨论了遗传进化技术在数据挖掘中的应用。     

遗传算法在决策支持系统和数据挖掘中的应用

决策支持系统和数据挖掘技术的应用已深入到企业管理、金融、办公及日常生活等各个领域。使用原先决策支持系统中的传统方法已远远不能满足决策者的需要，从而出现许多新技术新方法来辅助和完善决策支持过程。文中在介绍遗传算法的基础上，提出了一种将遗传算法与决策支持系统相结合的观点，阐述了基于遗传算法的决策支持系统的模型设计，且深入讨论了遗传进化技术在数据挖掘中的应用。     

决策支持系统在生态环境监测与管理中的应用

决策支持系统是综合利用各种数据、信息、知识和模型技术，辅助决策者解决决策问题的人机交互系统，根据研究区生态环境的空间组合关系建立模型，将环境监测与管理技术与决策支持系统的思想相结合建立环境资源决策支持系统，并设计开发生态环境监测与管理智能决策支持系统（EMIDSS），提出资源合理利用及环境整治的方案。     

卫星电源系统的有向图分层诊断方法

在卫星电源故障诊断问题的研究中,针对系统的知识获取难问题,提出了一种将有向图和CLIPS专家系统相结合的分层诊断方法。这种方法利用有向图知识描述容易和CLIPS推理引擎快速的优势,设计了一个以事实描述系统模型知识的自定义模板结构,同时采用有向图分层策略减小故障搜索空间,然后利用CLIPS提供的快速匹配算法完成诊断推理过程,最后结合已有的专家经验知识给出卫星电源的故障诊断结果。实验结果表明,新方法具有很好的准确性和快速性。     

基于本体的网络空间决策支持系统研究*

为了不同的空间决策,往往需要建立相应的空间决策支持系统,在这些空间决策支持系统中,大量的空间数据和模型是可以被重复使用的,因此提出了一种基于本体的空间决策支持系统。该系统能够高效、自动地利用互联网中存在的各类异构空间信息与分析资源来支持空间决策;此外,本系统还提出了一种灵活的体系架构来解决空间决策中存在的语义问题。     

The impact of model performance history information on users' confidence in decision models: An experimental examination

Effective decision support systems must supply decision makers with information that allows them to make correct judgments. Unfortunately, human intuitive judgments are subject to a number of biases. Among the judgments that a user of a decision support system must make is the selection of an appropriate model. When a decision maker is presented with a history of a model's usage and frequency of success during that usage, the decision maker must judge how confident he/she is in the output that comes from that model. We show, in a laboratory setting using 75 student subjects and 48 managers, that decision makers can be manipulated into irrational confidence levels. In a corporate setting, over- and under-confidence will result in either overreliance on unreliable models or failure to take advantage of a useful tool.     

基于CLIPS的智能无人飞艇故障诊断专家系统开发

针对智能无人飞艇的故障诊断问题,设计开发了一套基于CLIPS框架的故障诊断专家系统。首先,根据诊断专家的知识进行故障分类并建立故障树;其次,基于CLIPS工具设计了智能无人飞艇的故障事实库和规则库。然后采用静态链接的方式将CLIPS框架嵌入到C++中,并设计了"路由跳转"功能,实现了用户输入与CLIPS的数据交换接口,并利用MFC框架开发了相应人机交互界面。该智能无人飞艇故障诊断专家系统的开发,改善了现阶段人工故障诊断的不规范及效率低下等问题,为智能无人飞艇的故障诊断、分析和排除提供了平台和支持技术。     

基于专家系统的CODOG动力系统实时诊断的研究

讨论了运用专家系统ＣＬＩＰＳ结合高级编程语言Ｖｉｓｕａｌ Ｂａｓｉｃ实现实时故障诊断的一种方法。利用高级语言开发应用程序及专家知识库,并通过调用ＣＬＩＰＳ动态链接库,实现ＣＯＤＯＧ动力系统的状态监测、故障诊断。     

Development of a decision support system for robot selection

With the availability of more different robot types and models along with their separate specifications, selecting the most appropriate robot is becoming more difficult and complicated for companies. Furthermore, a common set of robot selection criteria is not available for the decision makers. In this study, a two-phase robot selection decision support system, namely ROBSEL, is developed to help the decision makers in their robot selection decisions. In development of ROBSEL, an independent set of criteria is obtained first and arranged in the Fuzzy Analytical Hierarchy Process (FAHP) decision hierarchy. In the first elimination phase of the decision support system, the user obtains the feasible set of robots by providing limited values for the 15 requirements. ROBSEL, then, uses FAHP decision hierarchy to rank the feasible robots in the second phase. ROBSEL is illustrated and tested and several critical issues in its practical usage are explored in the paper. The applications of ROBSEL show that ROBSEL is a useful, practical and easy to use robot selection tool and improves robot selection decisions in the companies.     

专家系统在火电厂汽包水位高报警诊断中的应用

为了及时、方便地根据火电厂的报警信息诊断出故障原因,使用Visual C 和专家系统工具CLIPS开发了火电厂报警诊断专家系统.给出了该系统的总体结构并介绍了其功能.同时详细说明了汽包水位高报警诊断的实现过程.实践证明该系统界面友好,功能完善,知识库易于维护和更新.     

Ovarian cancer diagnosis using a hybrid intelligent system with simple yet convincing rules

Ovarian cancer is the ninth most common cancer among women and ranks fifth in cancer deaths. Statistics show that the five-year survival rate is greater than 75% if diagnosis occurs before the cancer cells have spread to other organs (stage I), but it drops to 20% when the cancer cells have spread to upper abdomen (stage III). Therefore, it is crucial to detect ovarian cancer as early as possible and to correctly identify the stage of the cancer to prevent any further delay of appropriate treatments. In this paper, we propose a novel self-organizing neural fuzzy inference system that functions as a reliable decision support system for ovarian cancer diagnoses. The system only requires a limited number of control parameters and constraints to derive simple yet convincing inference rules without human intervention and expert guidance. Because feature selection and attribute reduction are performed during training, the inference rules possess a great level of interpretability. Experiments are conducted on both established medical data sets and real-world cases collected from hospital. The experimental results of our proposed model in ovarian cancer diagnoses are encouraging because it achieves the most number of correct diagnoses when benchmarked against other computational intelligence based models. More importantly, its automatically derived rules are consistent with expert knowledge.     

基于工程决策的专家系统模型设计与研究

工程决策的影响因子和参数繁多且复杂,为提高工程决策的可用性和准确性提出基于工程决策的专家系统模型。模型根据现有数据模型结合实际需求,在关系数据内部形成知识支撑环境模型,采用框架和产生式规则相结合的方法,将推理过程与专家知识库结合,并提出一种综合评估方法为支持,辅助生产方案设计和措施调整。以油田实际生产现状为例,给出了相应油田异常井措施调整方案的推理过程,完成了模型的实例设计和实现,达到了提供辅助决策以提高决策可用性和准确性的目的。     

An expert system for flow routing in a river network

Flow routing in a river network is one of the most important parts in the domain of water resources and hydrology. There are different characteristics in the different river networks. The mathematical models adopted to deal with the flow routing have their own advantages respectively. Thus a suitable model should be selected to solve the problem of flow routing on a specially appointed river network. But this selection is very difficult and requires highly specialized knowledge and expertise about the models. It is not easy and not appropriate for a civil engineer to spend much time in learning how to select a suitable model and how to manipulate it. Recent developments in mathematical model of flow routing and artificial intelligence have rendered it possible to construct an expert system to help civil engineers make this kind of decision. An expert system is addressed to handle this decision-making in this paper. The way for manipulation of the selected model and whether or not the interbasin rainfall-runoff should be considered are integrated into the system too. VP-Expert is employed as the shell of this expert system. The expert system has been tested on the Changtan watershed, north Guangdong province of China.     

An integrated expert system/operations research approach for the optimization of waste incinerator siting problems

This research aims at developing an integrated decision support system for the optimization of waste incinerator siting problems. In this integrated approach, both expert system and operations research techniques are used to model the siting problems of waste incinerator. Furthermore, an expert decision support system (EDSS) is implemented for the above problem and thus providing the decision makers a useful tool for decision-making. This EDSS is based on multi-criteria decision analysis in finding the best incinerator site by minimizing costs and environmental impacts. The proposed approach identifies a hierarchy of objectives for the siting problem. First of all, several potential sites need to be screened as a set of feasible alternative sites. Second, those alternative feasible sites will be further evaluated via the multi-criteria decision making methods. For the evaluation process, we solve a 0/1 combinatorial optimization problem at the upper level and proceed the multi-attribute utility function at the lower level to get the optimal solutions. An empirical application of a real world waste incinerator site selection existing in Taichung City, Taiwan is followed in the end. Computational results both of the cost minimization and of the whole systems are also provided.