基于粗糙集和粒子群优化神经网络的智能决策方法

针对多属性决策中的高维、非线性问题,提出一种基于粗糙集和粒子群优化神经网络的智能多属性决策方法.该方法利用粗糙集对多属性决策问题的条件属性进行约简,利用粒子群算法训练神经网络的权重和阈值形成粒子群优化神经网络模型,约简后的属性数据进入粒子群优化神经网络的智能决策系统.实证结果表明,该方法具有较好的泛化能力,与标准支持向量机、遗传神经网络等方法相比,该方法具有一定的优势.     

Anytime Decision Making Based on Unconstrained Influence Diagrams

Unconstrained influence diagrams extend the language of influence diagrams to cope with decision problems in which the order of the decisions is unspecified. Thus, when solving an unconstrained influence diagram, we not only look for an optimal policy for each decision but also for a so‐called step policy specifying the next decision given the observations made so far. However, due to the complexity of the problem, temporal constraints can force the decision maker to act before the solution algorithm has finished and, in particular, before an optimal policy for the first decision has been computed. This paper addresses this problem by proposing an anytime algorithm that at any time provides a qualified recommendation for the first decisions of the problem. The algorithm performs a heuristic‐based search in a decision tree representation of the problem. We provide a framework for analyzing the performance of the algorithm, and experiments based on this framework indicate that the proposed algorithm performs significantly better under time constraints than dynamic programming.     

Using Fine-Grain Threads and Run-Time Decision Making in Parallel Computing

Programming distributed-memory multiprocessors and networks of workstations requires deciding what can execute concurrently, how processes communicate, and where data is placed. These decisions can be made statically by a programmer or compiler, or they can be made dynamically at run time. Using run-time decisions leads to a simpler interface—because decisions are implicit—and it can lead to better decisions—because more information is available. This paper examines the costs, benefits, and details of making decisions at run time. The starting point is explicit fine-grain parallelism with any number (even thousands) of threads. Five specific techniques are considered: (1) implicitly coarsening the granularity of parallelism, (2) using implicit communication implemented by a distributed shared memory, (3) overlapping computation and communication, (4) adaptively moving threads and data between nodes to minimize communication and balance load, and (5) dynamically remapping data to pages to avoid false sharing. Details are given on the performance of each of these techniques as well as on their overall performance for several scientific applications.     

Group Decision Making on Urban Planning Using Desktop Multimedia Conferencing

Recent developments on multimedia systems and networking technology show that using desktop multimedia conferencing for group decision making on wide area networks such as the Internet is possible. In this paper we review the design, hardware and software requirements and organizational issues in a desktop multimedia conferencing system. We draw on our experiences from multiple multimedia conferences on the Internet and in particular we focus on a case study on urban planning using desktop multimedia conferencing on the Internet. Further we discuss implications for further research on desktop multimedia conferencing.     

Rationality in Information Systems Support to Decision Making

Management information systems serve business organizations by providing information for decision making. Various types of systems serve different types of decision contexts. The philosophic basis of information system support is discussed. The rational (or normative) philosophy is widely used, and appears in business theory in the form of agency theory and transaction cost analysis. While this approach has been valuable in some contexts, there are other contexts where the rational approach has limited in utility for real business decision making. Decision makers need to consider subjective factors to enable them to cope with the high levels of uncertainty, incomplete understanding, and imperfect data typical of dynamic open systems. There are alternative philosophies upon which to base decision-making that are appropriate for specific decision contexts. Churchman identified empirical, multi-perspective frameworks, dialectic, and cause-and-effect inquiring systems as alternatives to the rational (normative) system. A number of information system tools, such as decision support systems, expert systems, and group support systems can be supported by models based on philosophies other than rational models. A more empirically based philosophy, with decision-makers balancing hypothesis generation and observations of performance, is often more appropriate. The relationship between Churchman's inquiring systems and information system types are discussed.     

A New Generalized Pythagorean Fuzzy Information Aggregation Using Einstein Operations and Its Application to Decision Making

The objective of this article is to extend and present an idea related to weighted aggregated operators from fuzzy to Pythagorean fuzzy sets (PFSs). The main feature of the PFS is to relax the condition that the sum of the degree of membership functions is less than one with the square sum of the degree of membership functions is less than one. Under these environments, aggregator operators, namely, Pythagorean fuzzy Einstein weighted averaging (PFEWA), Pythagorean fuzzy Einstein ordered weighted averaging (PFEOWA), generalized Pythagorean fuzzy Einstein weighted averaging (GPFEWA), and generalized Pythagorean fuzzy Einstein ordered weighted averaging (GPFEOWA), are proposed in this article. Some desirable properties corresponding to it have also been investigated. Furthermore, these operators are applied to decision‐making problems in which experts provide their preferences in the Pythagorean fuzzy environment to show the validity, practicality, and effectiveness of the new approach. Finally, a systematic comparison between the existing work and the proposed work has been given.     

An Evidential Axiomatic Design Approach for Decision Making Using the Evaluation of Belief Structure Satisfaction to Uncertain Target Values

Axiomatic design (AD) provides a general theory for system and product development. In recent years, the principles of AD have been successfully applied to the decision‐making field, and derived a fuzzy AD approach for fuzzy decision‐making environment. In this work, the interest is paid on the theoretical developments and applications of AD in the uncertain environment expressed by Dempster–Shafer evidence theory. Based on the concept of belief structure satisfaction to uncertain target values, an evidential AD approach is proposed for decision making by combining the independence axiom and information axiom of AD with the framework of Dempster–Shafer theory. An illustrative example has demonstrated the effectiveness of the proposed approach. This work, on the one hand, has successfully generalized the principles of AD to the Dempster–Shafer uncertain environment; on the other hand, it has presented a successful application of the concept of belief structure satisfaction.     

Fuzzy Production Planning and its Application to Decision Making

This paper presents new methods for solving a production-planning problem. First the modified s-curve membership function as a methodology is constructed. Then fuzzy production planning problems with vagueness parameters alpha and fuzzy objective coefficients, fuzzy technical coefficients and fuzzy resource variables are outlined. The objective of this paper is to find a satisfactory solution for optimal profit in which vagueness is playing major factor in selecting the solution. Finally a practical application of decision-making in production planning is illustrated.     

基于Vague集模糊推理的多评价指标模糊决策方法

目前在智能领域中对Vague集的研究已越来越广泛与深入,并运用于决策问题中,有学者已把Vague集用于多评价指标的模糊决策中,但其决策方法在某些时候却难以得到目标。为此,本文提出了一个基于Vague集模糊推理的多评价指标模糊决策方法。在这个方法中,从基于Vague集的模糊推理的观点来看待模糊决策问题。将评价指标和候选方案之间的关系用一组基于Vague集的推理规则来表示,将决策者的要求用一组Vague集来表示,经过模糊推理等过程最后得到决策结果。然后还给出了一个实例说明这种多评价指标模糊决策方法。这个基于Vague集模糊推理的多评价指标模糊决策方法的提出为决策系统提供了一个有用的工具。     

Group Decision Making in Information Systems Security Assessment Using Dual Hesitant Fuzzy Set

Network information system security has become a global issue since it is related to the economic development and national security. Information system security assessment plays an important role in the development of security solutions. Aiming at this issue, a dual hesitant fuzzy (DHF) group decision‐making (GDM) method was proposed in this paper to assist the assessment of network information system security. A systemic index containing four aspects was established including organization security, management security, technical security, and personnel management security. The DHF group evaluation matrix was constructed based on the individual evaluation information from each expert. Some power average operator–based DHF information aggregation operators are proposed and used to fusion the performance of each criterion for information systems. The advantage of these operators is that they can describe the relationship between the indexes quantitatively. Finally, a case study about information systems security assessment was presented to verify the effectiveness of proposed GDM methods.     

犹豫模糊图及其在多属性决策中的应用*

犹豫模糊集作为定量描述犹豫不决的有效工具,通过同时处理不确定性信息中的犹豫性与模糊性,解决犹豫不决背景下的多属性决策问题.文中针对属性值为犹豫模糊数的多属性决策问题,研究基于模糊图论的相关模型与多属性决策方法.首先,提出犹豫模糊图的概念和部分常见运算规则.然后,构建基于犹豫模糊图的一般性多属性决策方法.最后,通过具体算例和对比性分析验证文中方法的合理性.     

群决策中两类判断矩阵的一种集成方法

研究群决策中不同偏好信息形式的集成方法。根据多个决策者给出关于方案的两类偏好信息－Fuzzy判断矩阵和AHP判断矩阵,建立了能够集成这两类偏好信息的最优化模型,通过求解该模型可直接得到每个方案的参考排序列,并使方案的排序结果最大程度地反映每个决策者的偏好。     

Use of Multi-Media Courseware to Teach Real-World Decision Making Skills

We combined the case study approach and information technologies to create a multi-media courseware that brought real-world decision making from engineering industry into the classrooms. This paper describes the process of developing the CD-ROM courseware, details of classroom administration, and results of measuring the effectiveness of using the courseware in classes. This courseware was selected as the Premier Courseware of 1998 by NEEDS and John Wiley and Sons through a rigorous application and review process. Evaluation results of the use of the courseware in classrooms show that it enhanced classroom experience of students and helped them understand how decisions were made in the real-world. It also enhanced their higher-level cognitive skills. We expect that widespread use of multi-media courseware build on similar principles could lead to significant changes in the way students are educated.     

VC中用Word生成随钻测量报告的一种方法

在定向钻进工作中,每个钻孔都有大量的测量数据,为了数据管理的方便,结果需要以Word文档的形式提供.对于重复性的测量工作,每次手工编写测量报告,既浪费时间又容易出错.因此,介绍一种在Visual Studio 6.0中利用word模板自动生成随钻测量报告的方法.     

期权定价理论在风险投资决策中的应用

在研究了风险投资的含义和基本特点的基础上，介绍了传统的投资决策方法即净现值法和内部收益率法的基本原理，并且指出现有的建立在净现值法基础之上的评价方法由于难以操作或不符合风险投资的特点，很难对风险投资项目进行有效的评价。在对风险投资行为特征进行深入分析的基础上，认为风险投资具有期权性质，提出了一种基于B1ack-Scholes定价公式的风险投资项目评价方法，从而有效克服了传统净现值法的局限，增加了风险项目投资决策的合理性和科学性。     

Using Decision Trees to Construct a Practical Parser

This paper describes a novel and practical Japanese parser that uses decision trees. First, we construct a single decision tree to estimate modification probabilities; how one phrase tends to modify another. Next, we introduce a boosting algorithm in which several decision trees are constructed and then combined for probability estimation. The constructed parsers are evaluated using the EDR Japanese annotated corpus. The single-tree method significantly outperforms the conventional Japanese stochastic methods. Moreover, the boosted version of the parser is shown to have great advantages; (1) a better parsing accuracy than its single-tree counterpart for any amount of training data and (2) no over-fitting to data for various iterations. The presented parser, the first non-English stochastic parser with practical performance, should tighten the coupling between natural language processing and machine learning.