A knowledge based decision support system for computer performance management

Computer systems managers make decisions about hardware and software selection, performance evaluation, capacity planning, and other resource variables on the basis of factual data, accounting data, subjective judgements, and assumptions about the resource consumption of the jobs being run. The importance of computer resource planning calls for effective support methods. A Knowledge-Based DSS (KBDSS) will be able to assist managers in making these policy decisions by utilizing knowledge of the existing configuration and its capabilities, the organizational computing environment, available external resources, and their suppliers. Combining procedural and declarative methods, such a KBDSS may provide early warning of possible bottlenecks, forecast growth of hardware usage, and employ knowledge based inferencing to suggest suitable remedial actions to the systems manager. This paper presents a KBDSS for supporting computer resource planning decisions using a procedural/declarative framework, and illustrates the system's usage aspects.     

三角模糊数互补判断矩阵排序的最小方差法

研究偏好信息为三角模糊数互补判断矩阵形式给出的方案排序方法.根据三角模糊数互补判断矩阵完全一致性的概念,建立了一个基于最小方差的非线性规划模型.通过求解该模型,得到三角模糊数互补判断矩阵的权重向量,并利用三角模糊数排序公式对决策方案进行排序.最后通过算例分析表明了所提出的方法是可行而有效的.     

A group decision making framework based on fuzzy VIKOR approach for machine tool selection with linguistic information

Computer numerical control (CNC) machines are used for repetitive, difficult and unsafe manufacturing tasks that require a high degree of accuracy. However, when selecting an appropriate CNC machine, multiple criteria need to be considered by multiple decision makers. In this study, a multi-criteria group decision making (MCGDM) technique based on the fuzzy VIKOR method is developed to solve a CNC machine tool selection problem. Linguistic variables represented by triangular fuzzy numbers are used to reflect decision maker preferences for the criteria importance weights and the performance ratings. After the individual preferences are aggregated or after the separation values are computed, they are then defuzzified. In this paper, two algorithms based on a fuzzy linguistic approach are developed. Based on these two algorithms and the VIKOR method, a general MCGDM framework is proposed. A CNC machine tool selection example illustrates the application of the proposed approach. A comparative study of the two algorithms using the above case study information highlighted the need to combine the ranking results, as both algorithms have distinct characteristics.     

Towards an evaluation framework for knowledge management systems

In this paper we develop an evaluation framework for Knowledge Management Systems (KMS). The framework builds on the theoretical foundations underlying organizational Knowledge Management (KM) to identify key KM activities and the KMS capabilities required to support each activity. These capabilities are then used to form a benchmark for evaluating KMS. Organizations selecting KMS can use the framework to identify gaps and overlaps in the extent to which the capabilities provided and utilized by their current KMS portfolio meet the KM needs of the organization. Other applications of the framework are also discussed.

A novel meta-heuristic based method for deriving priorities from fuzzy pairwise comparison judgments

This paper proposes a new method to derive the priority vector from fuzzy pairwise comparison matrices. Unlike several known methods, the proposed method derives crisp weights from consistent and inconsistent fuzzy comparison matrices. Therefore, the crisp weights obviate the need of additional aggregation and ranking procedures. To derive the priority vector, a Modified Fuzzy Logarithmic Least Square Model (MFLLSM) is proposed. In order to solve the MFLLSM, a framework based on genetic algorithm is proposed. In the proposed framework, a heuristic algorithm of population initialization, a heuristic algorithm for simulating fuzzy numbers and a heuristic algorithm of fitness evaluation are proposed.The solution of the prioritization problem requires finding priorities such that their ratio approximately satisfies the initial judgments. Computational results reveal the superiority of the proposed method in comparison with five well known methods of literature from the viewpoint of satisfaction of initial judgments by the obtained priority vector. It is shown by ten different examples that the deviation of the priorities ratio from initial judgments in the proposed method is less than five existing methods of literature. In addition, unlike several methods of literature, the proposed method considers fuzzy judgments represented by both triangular and trapezoidal fuzzy numbers. Furthermore, the proposed method for the first time considers judgments represented by triangular shaped fuzzy numbers and trapezoidal shaped fuzzy numbers which are discussed in the paper.     

三角模糊数多属性决策在软件项目风险评估中应用

风险评估是软件项目风险管理的基础。基于软件项目风险评估目标及相关文献分析,构建了风险评估的准则体系,并将三角模糊数多属性决策方法应用于软件项目风险评估中。通过实例说明了该方法运用于软件项目风险评估的具体过程,并验证了其合理性和可操作性。     

A method based on distance measure for interval-valued intuitionistic fuzzy group decision making

In this paper we introduce some relations and operations of interval-valued intuitionistic fuzzy numbers and define some types of matrices, including interval-valued intuitionistic fuzzy matrix, interval-valued intuitionistic fuzzy similarity matrix and interval-valued intuitionistic fuzzy equivalence matrix. We study their properties, develop a method based on distance measure for group decision making with interval-valued intuitionistic fuzzy matrices and, finally, provide an illustrative example.     

信息安全风险模糊群决策评估方法

信息安全风险评估是对信息安全进行风险管理的最根本依据,信息安全风险评估的客观性和准确性对保障信息系统安全起着重要作用。针对信息安全风险数据难以获取、不确定性较多的特点,给出了一种基于模糊评价矩阵的信息安全风险群决策评估方法。首先将语言评价转化为定量的模糊评价,利用三角模糊数来建立信息安全风险的可能性矩阵和损失矩阵,然后通过对专家意见的集结,得到信息安全风险矩阵。其次给出了三角模糊数风险矩阵正理想解和负理想解的选取方法,以及风险严重程度的比较依据,对威胁的风险大小进行分析与评判。最后通过一个算例对该方法进行了说明。     

A soft computing method of performance evaluation with MCDM based on interval-valued fuzzy numbers

This study presented a new performance evaluation method for tackling fuzzy multicriteria decision-making (MCDM) problems based on combining VIKOR and interval-valued fuzzy sets. The performance evaluation problem often exists in complex administrative processes in which multiple evaluation criteria, subjective/objective assessments and fuzzy conditions have to be taken into consideration simultaneously in management. Here, the subjective, imprecise, inexact and uncertain evaluation processes are modeled as fuzzy numbers by means of linguistic terms, as fuzzy theory can provide an appropriate tool to deal with such uncertainties. However, the presentation of linguistic expressions in the form of ordinary fuzzy sets is not clear enough [15] and [21]. Interval-valued fuzzy sets can provide more flexibility [4] and [14] to represent the imprecise/vague information that results, and it can also provide a more accurate modeling. This paper presents the interval-valued fuzzy VIKOR, which aims to solve MCDM problems in which the weights and performances of criteria are unequal by using the concepts of interval-valued fuzzy sets. A case study for evaluating the performances of three major intercity bus companies from an intercity public transport system is conducted to illustrate the effectiveness of the method.     

A framework for conducting political event analysis using group support systems

Corporations seeking to expand their operations internationally often encounter certain political events that they do not encounter domestically. Political events are those events that may occur because of the actions or decisions made by certain political actors having influence in a region. Such events include corruption, currency fluctuations, and civil unrest. However, obtaining information and insight about such events from local knowledgeable persons is often difficult due to authoritarian governments and/or cultural environments that discourage open criticism. We present a framework for using group support systems (GSS) under such conditions. The framework consists of methods that can be employed depending on the number of events (unidimensional or multidimensional) and time periods (static or dynamic) of interest. Each method is illustrated with local Hong Kong business executives addressing the future of Hong Kong as a desirable place to conduct multinational operations.     

Knowledge management systems and organizational knowledge processing challenges: A field experiment

This paper investigates the appropriateness of knowledge management system (KMS) designs for different organizational knowledge processing challenges. Building on the theory of task-technology fit (TTF), we argue that different KMS designs are more effective for different knowledge tasks. An exploratory field experiment was conducted in the context of Internet-based knowledge sharing services to provide empirical support for our hypotheses. The results of our experiment show that a KMS designed to support the goal GENERATE is more appropriate for divergent type knowledge problems because of its affordances for iterative brainstorming processes. Conversely, for convergent type knowledge processing challenges, a KMS with the goal CHOOSE that supports the ability to clarify and to analyze is more effective.     

一种基于三角模糊数的VANETs机会路由算法*

分析了现有车用自组织网络（VANETs）的路由算法,提出一种新的基于三角模糊数的机会路由算法。新算法将转发结点距离目标结点的距离、到达目标结点的方向、行驶速度向量、重传次数、车流状况等因素作为目标函数进行分析计算,采用熵权系数法确定各因素权重。路由过程中,贪婪选择向量值最大的节点转发数据包;遇到网络不连续时,将采用“存储－携带－转发”的机会路由策略。仿真结果表明,该算法能够较好的适用于VANETs各种场景。     

改进的三角模糊数互反判断矩阵排序算法研究

研究了模糊层次分析法中以三角模糊数为元素的互反判断矩阵排序方法问题,提出一种改进模糊概率算法。采用改进的满意一致性判断指标对互反判断矩阵判断与修正;用模糊概率算法将判断矩阵特征向量中的三角模糊数转换成准确值,最终得出排序向量。实例分析结果表明,排序向量更加趋近理想判断,算法更具准确性。     

Measures of success for lone-user management support systems

Abstract. Management support sytems (MSS) are systems that involve the use of information technologies to support management lone-user MSS are such systems used by managers acting alone, whether the systems have been developed for an individual's exclusive use or for more than one user. Information systems research has been hampered by the lack of widely agreed measures of success. There are two main reasons for this. First, there has been a lack of rigour in the presentation of research findings, particularly in the definition of the types of system that have been investigated. This is particularly the case with MSS. Second, there is often no direct way of determining the effect of an MSS on the goals of an organization in the midst of many other concurrent factors. A classification of lone-user MSS is first given. The many, often indirect, measures of success that have been suggested are then charted. These are then incorporated into a hierarchical framework of organizational goals and intra-MSS measures. Finally, appropriate measures of success to use with the two major classes of MSS are suggested.     

基于改进三角模糊数的网络安全风险评估方法*

采用改进的德尔菲法对网络安全指标进行选取,在评价指标权重确定上,针对传统的AHP（层次分析法）权重确定方法的缺点,提出了改进的三角模糊数评价IFAHP方法。最后,设计并实现了一个网络安全评价原型系统,并采用二级模糊综合评价对网络系统的安全性进行了评估。实验结果表明,该方法能有效地解决AHP方法的主观随意性和一致性验证的问题,提高网络安全评价的客观性和有效性。     

A study of group support systems and the intergroup setting

In this study, we explore the supporting role of group support systems (GSS) in organizational workgroups that involve groups of distinct social identities. Intergroup processes become relevant and prevalent in such workgroups and trigger new issues. Anonymity is an important feature of GSS that concerns social influence in the intergroup setting. We report on the results of an experiment consisting of 20 workgroups. The enforcement of common fate and its impact on social influence are also examined. Our findings provide preliminary indication of the usefulness of GSS in the intergroup setting of organizational workgroups.     

Using the fuzzy multi-criteria decision making approach for measuring the possibility of successful knowledge management

This study develops a forecasting framework based on the fuzzy multi-criteria decision making (FMCDM) approach to help organizations build awareness of the critical influential factors on the success of knowledge management (KM) implementation, measure the success possibility of knowledge management projects, as well as identify the necessary actions prior to embarking on conducting knowledge management. Subjectivity, uncertainty and vagueness within the prediction process are dealt with using linguistic variables parameterized by triangular fuzzy numbers. By multiplying the importance weights of influential factors and the possible rating of success (failure), predicted success (failure) values are determined to enable organizations to decide whether to initiate knowledge management, inhibit adoption or undertake remedial improvements to increase the possibility of successful knowledge management project. The proposed approach is demonstrated using a real case involving a Taiwanese semiconductor engineering corporation.     

Computer-aided maintenance management systems selection based on a fuzzy AHP approach

Computerized maintenance management systems (CMMS) are common in today’s industries. CMMS can bring a large number of benefits, which include increased productivity, reduced costs, and effective utilization of the assets in any manufacturing and service producer. The list of CMMS that are available in the market has grown very rapidly during the last years. When purchasing a system, one that suits the specific needs and objectives of the company’s maintenance operations should be preferred. Several selection methods were proposed in literature. Up to now, no article has considered ambiguity and uncertainty factors when selecting effective CMMS. In addition, CMMS selection decisions involve the simultaneous consideration of multiple criteria, including tangible and intangible factors; prioritizing these factors can be a great challenge and a complex task. Therefore, no attempt has been made to incorporate fuzziness into multicriteria decision-making in the area of CMMS selection. This work proposes a fuzzy-based methodology for comparative evaluation of a number of CMMS alternatives. The proposal is based on the well-known multicriteria decision method called Analytical Hierarchy Process (AHP) with triangular numbers. An example is given to illustrate the proposed methodology. Finally, a software prototype for implementing this method was implemented. To illustrate and validate the proposed approach and the software prototype developed some details are presented and discussed.     

一类完全模糊非线性系统同伦法求解

在现有三角模糊数表示及模糊运算规则基础上,采用参数变换法对一类模糊非线性系统做变换,得到同解的确定非线性系统。采用同伦法求解该确定非线性系统,进而给出原模糊非线性系统的近似解,并给出了具体算例。     

基于三角模糊数的AHP-TOPSIS村庄下开采接续方案优选方法研究

为了研究在保证出煤量的条件下最大程度的减少采空区对村庄建筑的损害,合理安排采煤接续方案的问题。采用综合层次分析法(AHP)结合逼近理想解排序法(TOPSIS)的基础上引入模糊数学理论,建立了村庄下采煤地表建筑物损坏的模糊评价模型。解决了多属性评价指标融合问题和评价指标过硬问题。以辽源矿区龙家堡煤矿村庄下孤岛煤柱开采为例实施了该理论成果并得到了合理的技术结论。