面向复杂产品系统项目评价专家遴选方法研究

专家遴选是复杂产品系统(CoPS)项目科学评价过程中的重要决策问题,科学合理的遴选专家有利于CoPS项目的实现。CoPS项目的多领域知识集成性和项目任务的模糊不确定性,给项目评价的知识属性识别和专家遴选相对“小”领域的科学判断带来较大困难。在面向CoPS项目评价的专家遴选研究问题上,提出了包含技术领域和任务领域的二元知识分类表征方法,构建了基于直觉模糊相似度的专家知识关联度侧度模型,在此基础上建立了包含专家业绩评价和知识关联度的专家遴选多目标决策模型,并给出了一个航天领域电子元器件项目评价的实例。     

基于直觉模糊软集的群决策方法研究

研究了专家权重未知情况下基于直觉模糊软集的群决策问题.首先利用距离提出了一种基于直觉模糊软集的决策算法.然后通过考虑专家个体提供信息本身的不确定性和专家之间提供的信息间的一致性,定义了直觉模糊软集的知识测度和基于α-相似关系的一致度,由此提出了一种确定专家权重的方法.进而给出了一种基于直觉模糊软集的群决策算法.最后通过实例说明所提出算法是有效的与合理的.     

智能化英汉机译系统IMT/EC

IMT/EC是一个智能型机译系统,它实现了格文法分析与语义文法分析的有机结合,利用多种不同知识区分翻译过程中的多义性,同时还实现了译文文体的自动修饰。本文详细介绍IMT/EC的翻译处理机构的设计原理及一些主要的处理算法。     

智能图象数据库系统ISDBS

本文叙述我们实验室研制的智能图象数据库系统ISDBS,其中提出并实现了系统的智能设计、知识化横式、新型物理数据库结构、用于规划决策专家系统设计的知识表示语言IDL等一系列新型的关键理论和技术。该系统已成功地应用于黄土高原安塞地区的土地规划和东北松江河林场的森林资源管理。     

带有控制约束的不确定非线性系统的H_∞控制

研究了一类含有控制约束(饱和执行器)的不确定非线性系统的H_∞最优控制问题.首先,引入非二次型函数来解决控制受限的问题.然后借助二人零和微分对策理论研究H_∞最优控制问题,提出了模型自由的在线学习算法,仅仅通过在线获得的系统的状态信息而无需模型知识就能很好的解决H_∞控制问题.建立了执行网-评价网-扰动网三网络结构完成算法的在线实现.最后,利用李雅普诺夫(Lyapunov)稳定性理论给出了系统的稳定性分析,仿真算例验证了算法的有效性.     

线性系统的完全不变量,标准形实现与编码

线性定常系统的完全不变量的研究,不仅在代数上有理论意义,而且对系统的最小实现与辨识有重要应用价值.Popov 等给出了线性定常系统的完全不变量;一组完全不变量对应了系统的一种标准形.Bucy 等曾研究了由系统的 Markov 参数直接求得系统标准形的实现算法(称为标准形实现).Guidorzi给出了由系统输入输出数据得到系统标准形的实现算法与结构辨识算法.     

"马克威分析系统"推广应用评估会在沪进行

2004年12月30日,中国统计学会在上海主持召开了"马克威分析系统"推广应用评估会.中国统计学会、中国统计教育学会、中国人民大学、中国人民解放军信息工程大学、台湾辅仁大学、美国雪城大学等机构的专家应邀出席了会议.与会专家观看了"马克威分析系统"主要功能演示,查阅了该系统知识产权等相关文档,听取了关于"马克威分析系统"算法及计算结果比较分析报告.在此基础上,专家们一致认为,     

飞机故障模糊诊断专家系统的研究

运用飞机专家的知识和经验,模拟飞机专家解决问题的思维方式,建立了用来查找异常原因的智能性程序系统,从而为飞机的故障诊断维修工作提供了一种科学、可行的新方法.     

社会网络环境下基于“信任—知识”模型的风险性大群体应急决策方法

针对大群体应急决策专家之间信任关系及其传递引发的决策风险,以及由于大群体中个体偏好差异较大导致生成独立聚集等问题。首先,提出一个“信任—知识模型”对决策专家之间的信任关系进行集成和传递,并根据决策专家的信任风险偏好得出决策专家之间的信任知识度网络;其次,利用Louvain算法对信任知识度网络进行聚类,高效快速的获得若干个聚集,并用社会网络分析技术确定每个决策者和聚集的权重;然后对每个聚集中的决策者偏好进行集结,并综合决策者给出的信息对备选决策方案进行排序。最后,通过案例分析和对比验证了所提方法的合理性与有效性。     

面向电力虚拟社区的隐性知识云处理模型

当前电力虚拟社区中非结构化的隐性知识资源数量与日俱增,然而由于其中自由的问答交流模式,导致解决具体问题的隐性知识淹没于大量的无效信息中,电力相关从业人员难以快速从中获取适用性好的隐性知识;同时,随着电力虚拟社区的大规模扩张,激增的数据量将带来存储扩展性和快速检索的问题.为此提出一种面向电力虚拟社区的隐性知识云处理模型MPTKKM.模型以模式匹配算法为核心,设计了可以自动建立电力隐性知识应用情景描述关键词序列的隐性知识收集算法,采用分布式键值对的存储模式,并基于云计算技术实现了电力隐性知识检索.实验结果表明,提出的模型不但能自动收集适用性好的电力隐性知识,而且云检索算法表现出了良好的可扩展性.     

基于模糊层次综合评判法的高等学校生态校园评价

目前我国很多大学都致力于生态校园的建设,通过相关文献的学习,在综述了国内外生态校园的研究进展的基础上,构建了高等学校生态校园评价指标体系.将层次分析法和模糊综合评价法耦合形成一种新的方法模糊层次综合评判法(FAHP),运用层次分析法结合专家经验,借助于Expert Choice软件研究了生态校园指标体系的权重,并结合模糊综合评判法进行最后的评价定级.以河北工程大学东校园为例对本套指标体系和评价方法做了检验和分析,验证了其有效性.     

三好学生的模糊综合评选模型

通过分析目前三好学生评选中存在的不足之处 ,构建了三好学生综合评选指标体系 ,应用模糊综合评价理论建立了三好学生模糊综合评选模型 ,介绍了如何应用专家调查法来确定各指标的权重 .     

Expert systems as a tool for statistics: A review

The current state of using expert system (ES) techniques for statistics is expounded through the difficulties of defining the notion of statistical expert system (SES) and through several well-known examples. The main characteristics of statistical expertise, and particularly the important concept of strategy are emphasized. The current state of SESs is seen in the context of the global trend of the evolution of ES, i.e. within the growth of second generation expert system (SGESs). The knowledge base of these ESs represent an attempt to represent not only experts' knowledge but also the way experts acquire their expertise, thanks to the existence of an underlying model. We show through many examples how far SESs are and/or will be able to be SGESs.     

Robust Adaptive Identification of Fuzzy Systems with Uncertain Data

This study presents a method of adaptive identification of parameters describing Sugeno fuzzy inference system in presence of bounded disturbances while maintaining the readability and interpretability of the fuzzy model during and after identification. This method do not require any a priori knowledge of a bound on the disturbance and noise and of a bound on the unknown parameters values. The method can be used for the robust and adaptive identification of slowly time varying nonlinear systems using fuzzy inference systems. The suggested method was used to build a fuzzy expert system that approximates the functional relationship between physical fitness and some of the measurable physiological parameters by their real measurements and opinion (human-experiences) of a medical expert.     

Expert and experiential knowledge in planning

The issue of expert and experiential knowledge has received increasing attention in conjunction with the contemporary surge in interest in post-positivist approaches in planning and policy-making. So far, few concrete methods have been put forward on how to evaluate these two types of knowledge in specific policy-making situations and thereby achieve their balanced use. This paper presents two approaches that can be used to derive expert and experiential knowledge. It describes their application to two case studies, one in Sweden and one in Italy, where expert and experiential knowledge were generated and used in urban development plans. It also proposes a method for evaluating and integrating the two types of knowledge.     

A knowledge-based multi-role decision support system for ore blending cost optimization of blast furnaces

Literature illustrates the difficulties in obtaining the lowest-cost optimal solution to an ore blending problem for blast furnaces by using the traditional trial-and-error method in iron and steel enterprises. To solve this problem, we developed a cost optimization model which we have implemented in a multi-role-based decision support system (DSS). On the basis of analyzing the business flow and working process of ore blending, we propose an architecture of DSS which is built based on multi-roles. This DSS construction pre-processes the data for materials and elements, builds a general database, abstracts the related optimal operations research models and introduces the reasoning mechanism of an expert system. A non-linear model of ore blending for blast furnaces and its solutions are provided. A database, a model base and a knowledge base are integrated into the expert system-based multi-role DSS to meet the different demands of data, information and decision-making knowledge for the various roles of users. A comparison of the results for the DSS and the trial-and-error method is provided. The system has produced excellent economic benefits since it was implemented at the Xiangtan Iron & Steel Group Co. Ltd., China.     

属性和专家客观权重未知的多值中智数群决策方法

针对评价信息为多值中智数的多属性决策问题,提出基于最小最大相似度求解属性权重与标准区间求解专家权重的方法.该方法首先根据最小最大模型求解属性权重,将初始评价矩阵集结为综合决策矩阵,其次利用数字分析法求得标准区间,根据各专家与标准区间的相似度确定专家权重,再对综合评价矩阵集结得各方案的综合评价值,对综合评价值排序得最优方案,最后用实例说明了方法的有效性和适用性.     

Integration of AI and OR Techniques for Computer-Aided Algorithmic Design in the Vehicle Routing Domain

This paper shows how tools and techniques of artificial intelligence can be successfully integrated into a computer system working in the vehicle routing domain. The aim of this system, called ALTO, is to facilitate the development of routing algorithms for transportation vehicles. In this paper, we describe the general algorithmic framework and the rich interface provided by the system to the expert algorithm designer. We also introduce a methodology for acquiring useful knowledge in the domain, based on examples of successful and unsuccessful problem-solving strategies. With such knowledge, ALTO would then be capable of actively supporting the algorithm designer by suggesting good candidate algorithms for solving new problems.