竞争性电子采购智能群决策支持系统设计

电子商务时代,通过电子采购提高效率降低成本成为大势所趋,电子采购已是重要的研究领域。随着电子采购环境的日趋复杂,采购方的决策管理水平亟待提高。为辅助采购方更好地完成采购决策,文中基于决策支持技术设计了竞争性电子采购智能群决策支持系统。该系统利用网络便捷的信息通信实现了群体协同决策,通过智能数据处理实现了智能决策。该系统可提供复杂采购问题的决策支持。     

基于Agent的组织决策支持系统SG—ODSS的研究与应用

基于Agent协作交互的组织决策支持系统(ODSS)的研究是智能信息系统研究的热点.本文在阐述了组织决策支持系统和智能Agent基础上,提出了基于Agent协作交互的SGODSS系统的结构和组成,包括组织Agent,处理AAgent组、通信Agent等,并介绍了该系统在某大型电器公司的应用.     

供水调度中实现决策支持的方法研究

针对供水调度系统在决策支持方面的不足,本文提出利用SQL Server Analysis Services在OLAP及数据挖掘方面的技术,建立数据仓库、OLAP和数据挖掘三者相结合的决策支持系统的方案,讨论了基于Analysis Ser-vices实现供水调度决策支持系统的技术.     

面向高层决策支持决策全过程的应用系统集成

在实际开发工作中,DSS常常只对决策制定过程中的抉择阶段提供支持,很少涉及到决策制定过程中的另外两个不可分割的阶段：情报收集阶段和方案设计阶段,并且提供的支持大多数属干定量分析,很少有定性分析．表文分析了ES与DSS、EIS和ESS可能的集成方式,并认为不同类型的应用系统能对决策制定过程的不同阶段提供不同的支持．这些应用系统不但可以独立地为企业管理和决策活动服务,而且它们之间在数据处理上存在着一定的逻辑关系,这种逻辑关系为企业中信。糸统的集成奠定j基础．在此基础上,论文对应用系统进行重新分类,并提出了面向     

基于商务智能的税务征管决策支持研究

我国税务信息化经过多年发展已积累了大量数据,基于商务智能技术的税务决策支持系统可以充分利用这些数据支持税收征管工作.本文介绍了商务智能技术在税务分析和税收征管决策中的支持应用,以及构建基于商务智能的税务决策支持系统的关键问题:数据库统一规划、模型的构造、知识库的建设、业务规则库的建设、缺乏相关复合型人才.     

基于数据挖掘的税收决策支持系统设计

提出了一种基于数据挖掘、0LAP以及XML的税收决策支持系统的设计方案,以期解决现行税收管理信息系统存在的若干问题.在分析了现有税收管理信息系统的现状后,讨论了0LAP、数据挖掘和数据仓库技术在税收决策支持系统上的应用,并结合XML技术和多维数据模式设计的思想,勾画了一个税收决策支持系统的架构.     

企业生产综合计划的优化编制与决策支持研究

针对我国社会主义市场经济体制的特点,将市场和顾客需求引入生产计划评价指标体系,建立了一种基于规划、优化、反馈调整的3阶段生产综合计划优化编制方法,并给出了相应的决策支持系统结构框架     

基于文本挖掘和自动分类的法院裁判决策支持系统设计

在许多大陆法系国家,不断产生的新型法律关系使得成文法无法及时制定和修改的缺陷逐渐显现。与此同时,世界各国纠纷诉讼的数目也在急剧增长,所以,很多国家面临如何在保证审判质量的前提下提高司法系统审判效率的问题。因此,在进行制度改革的同时,建立决策支持系统将会有效地辅助司法判决。本文以中国的医疗损害诉讼文本为例,使用文本挖掘和自动分类技术提出了一个法院裁判决策支持系统（CJ-DSS）,该系统可以依据以往判例预测新诉讼文本的判决结果：驳回与非驳回。结合案例,本文研究发现,组合特征提取法确实能够改进和提高分类器的分类性能,而且针对支持向量机（SVM）、人工神经网络（ANN）、K最近邻（KNN）三种不同的分类器,文档词频-卡方（DF-CHI）组合特征提取法对性能的改进程度有所差异,其中ANN的性能改进最高。除此之外,集成学习后该系统的分类性能更加稳定,显著优于单一分类器,F₁值达到93.3%。     

FINDING SYNERGY BETWEEN DECISION SUPPORT SYSTEMS AND EXPERT SYSTEMS RESEARCH

This article examines the potential for synergy between decision support systems (DSS) and expert systems research. Three predominant research traditions in DSS (applications, design, and technology) are examined and used as a basis to identify ways in which expert systems and DSS research interrelate. A range of emerging trends in DSS research that focus on these commonalities is discussed.     

COMPUTER-BASED SUPPORT OF ORGANIZATIONAL DECISION MAKING*

The central issue of this research is the extent to which computer facilities can be used to support organizational decision-making processes beyond mere performance of information retrieval. This depends upon the extent to which computers can be made to emulate human perceptual and judgmental processes. We present a framework for understanding these cognitive processes and examine how it applies to organizational decisions. Moreover, the framework furnishes a basis for the design of a generalized, intelligent problem processor. This processor is general in the sense of its ability to support a decision maker's activities, regardless of the decision maker's application area (e.g., urban planning, water-quality planning, etc.). It is intelligent in the sense of its ability to comprehend English-like queries and subsequently formulate models, interface appropriate data with those models, and execute the models to produce some facts or expectations about the problem under consideration.     

A PAVEMENT MANAGEMENT DECISION SUPPORT SYSTEM

We present a pavement management expert system developed by the University of Wisconsin-Madison and implemented within a geographical information system for the Wisconsin Department of Transportation. The system uses pavement data regularly collected on the state's 12,000 miles of highway to assist engineers, planners, and budget analysts' management decisions about pavements to be included in 6-year improvement and 3-year maintenance programs. The system has a three-layer architecture. The lowest level suggests treatments for each of a large number of small segments of highway. The middle layer aggregates segments, suggests alternative treatments, and estimates the cost of each. The top layer prioritizes the projects and incorporates them into intermediate-range plans. The geographical information system environment enables integration of existing databases within the system using a topologically structured geographic database and specialized software.     

AN EMPIRICAL EXAMINATION OF SOCIAL POWER IN TERMS OF DECISION THEORY1

The paper presents an extension of decision theory to the analysis of social power. The power of a person, A, over another person, B, is viewed in terms of the effect A has on B's decision. The analysis is based on the idea that B's decision regarding the performance of alternative behaviors is a function of 1) B's utility for the consequences of the behaviors and 2) B's subjective probabilities that the behaviors will lead to these consequences. In these terms, A's power over B lies in A's ability to mediate various consequences for B, contingent upon B's compliance or noncompliance. Subjects were asked to consider eight situations in which hypothetical individuals had to make a choice between two courses of action. In each situation another person (A) was attempting to induce the hypothetical individual (B) to choose one of the alternatives, while various situational factors were influencing B to choose the other alternative. The subjects were asked to consider B's utilities and subjective probabilities in each situation and to indicate whether or not B should comply with A and to make ratings of A's power. The decision theory analysis did well in predicting whether or not subjects would indicate that B should comply with A. Also, subjects generally were able to correctly specify whether A or the situational factors had more influence over B's decision. Finally, the subjects' ratings of A's power in the eight situations were highly related to the decision theoretic measure of power.     

A DECISION THEORY EXAMPLE IN FOOTBALL

In the 1967 Harvard-Cornell football game, Harvard was ahead 14–0 late in the game when Cornell scored two touchdowns. On both occasions, Cornell tried and failed on the two-point conversion attempt and lost the game 14–12. Postgame arguments were divided on the merits of Cornell's strategy. For this frequently occurring scenario in college football, we derive a maximum expected utility decision rule for the decision of kicking versus running/passing based on the relative utility of a win, a tie, or a loss and the probabilities of success with a kick as opposed to a run/pass.     

PREFERENCE MAPPING OF PERCEIVED INFORMATION STRUCTURE: IMPLICATIONS FOR DECISION SUPPORT SYSTEMS DESIGN

In a recent issue of this journal, Watkins [13] presented an approach for discovery of decision-maker perceptions of the complexity (dimensionality) of information items that might be supplied by a decision support system. Through use of multidimensional scaling and cluster analysis, relatively homogeneous groups of decision makers, sharing common perceptions of various information items, were formed. This prior research was referred to as a first step in suggesting that information reports could be tailored to groups of decision makers classified on the basis of common perceptions of information. The current research extends the prior study by evaluating decision maker preferences for information in a variety of decision-making scenarios in relation to the previously identified perceptions of the information. Based on the results of the study, conclusions are made which suggest that the tailoring of information to groups of decision makers should be based on both perceptions and preferences for information. Even so, it is demonstrated that the decision tasks have an impact on the preferences for information which may affect the attempt to tailor information to groups of decision makers.     

AN ADAPTIVE DECISION SUPPORT SYSTEM FOR ACADEMIC RESOURCE PLANNING

Institutions of higher learning are growing increasingly interested in the use of model-based approaches to their resource allocation problems. Recent modeling approaches, however, have failed to consider that resource allocation planning is not a well-structured decision process. Additionally, many decision makers are necessarily involved in the academic planning process and may assume dissimilar perspectives on the importance of achieving different goals and objectives. Furthermore, satisfactory allocation solutions can be expected to vary considerably from decision maker to decision maker as the individual's cognitive processes, perceptions, and evaluations are taken into consideration. This paper describes a decision support system (DSS) approach that attempts to adapt to a variety of academic decision makers with differing planning views in an environment of multiple conflicting objectives. This DSS, which was successfully tested on four academic decision makers in a large midwestern university, shows considerable promise for providing decision support to decision makers with varied problem-solving styles.     

基于管理问题理解的DSS智能构模理论框架研究

首先分析了目前DSS应用热潮减弱的深层原因,并综述了国内外模型构造现状及存在问题．在此基础上,首次提出了一个更加符合人类思维习惯的三层次智能构模理论框架,该理论框架由管理问题理解层、问题模型类匹配层和模型智能构造层三个层次组成,并给出了三个组成层次中的主要研究内容     

A MODEL-BASED DECISION SUPPORT SYSTEM FOR SCHEDULING LUMBER DRYING OPERATIONS

Raw lumber must be dried to a specified level of moisture content before it can be used to make furniture. This paper deals with a model-based decision support system (DSS) for a local furniture manufacturing company to assist its management in scheduling lumber drying operations. In addition to buying ready-to-use dried lumber from vendors at a premium, the company processes raw lumber in house using two production process that require various lengths of processing time in predryers and dry-kilns. Given the demand for various types of dried lumber over a specified planning horizon, the processing times and costs for each production process, technological restrictions, and management policies, the problem of interest is to satisfy the demand at a minimum cost. The DSS incorporates the mathematical formulation of this problem, is user friendly, maintains model and data independence, and generates the necessary reports, including loading and unloading schedules for the equipment.