基于模糊评判的Web服务评价模型

Web服务质量的评价是指导Web服务的选取与组合的主要手段,而目前的Web服务评价模型采用通用的服务评价属性作为评价因子,忽略了Web服务质量评价的多元性和模糊性。用基于模糊理论的方法描述Web服务评价模型,支持使用专业人员或领域专家的领域知识计算评价因子的权值分布。与其它Web服务评价机制相比较,该模型能更加准确、客观地反映实际情况,减少人为的主观随意性,对Web服务质量做出了合理的评价。     

基于模糊数学理论的信誉评估算法研究

针对信任评估的主观性、模糊性以及无法精确地描述和验证等问题,提出信誉评估算法.算法定义了信任度、隶属度、信任关系、关键属性以及模糊变换等基本概念和关键属性集U、代理集Y、评价集V、评价集矩阵R四个要素.根据模糊数学理论,将代理X的信任程度以及各代理对被代理的各关键属性的评估进行模糊变换,得到即将交易的代理Y的信任向量,并根据实际对原代理X的各信任值向量化,最终得到对代理X的信任值或信誉.实例表明,算法能用直观、简洁的语义定量地描述信任值,反映了实体之间信任的模糊性,解决了关于模糊性实体之间的信任建模问题,适用于电子商务、电子政务等领域.     

基于模糊理论的漏洞危害等级评估

针对安全漏洞危害难以量化评估的问题, 提出一种基于模糊理论的漏洞危害等级评估方法。使用层次分析法建立漏洞等级评估体系并计算漏洞评估影响因素的权重。利用模糊综合判断法对漏洞危害等级进行定量评价, 综合可利用性和安全影响两方面因素实现对漏洞危害的评估。实验结果表明该方法对于漏洞危害能够得到更加准确的评估结果。     

Soft fuzzy rough sets for robust feature evaluation and selection

The fuzzy dependency function proposed in the fuzzy rough set model is widely employed in feature evaluation and attribute reduction. It is shown that this function is not robust to noisy information in this paper. As datasets in real-world applications are usually contaminated by noise, robustness of data analysis models is very important in practice. In this work, we develop a new model of fuzzy rough sets, called soft fuzzy rough sets, which can reduce the influence of noise. We discuss the properties of the model and construct a new dependence function from the model. Then we use the function to evaluate and select features. The presented experimental results show the effectiveness of the new model.     

Selection of mobile value-added services for system operators using fuzzy synthetic evaluation

Following deregulation of the mobile phones market and liberalization of the telecommunications sector, the service sector for mobile phones is becoming increasingly saturated. Telecom operators are confronted with a sluggish user growth rate and a fall in the average revenue per user (ARPU). Mobile value-added services are expected to form mobile operators' strategy to make up for the dwindling revenues obtained from users. The purpose of this study is to provide an analytical tool to select the best mobile value-added service firm providing the most customer satisfaction. This study adopts a fuzzy synthetic evaluation method, using an analytic hierarchy process (AHP) to evaluate the performance of mobile value-added services system operators. This method can help consumers select the appropriate firm from the other consumers' opinions, and can help telecom operators to understand the market status of mobile value-added services as well as the prevailing consumer patterns.     

应用模糊综合评价进行智能手机评估建模

为了对市场上各种智能手机进行合理公正的评估,提出了基于变异系数法和加权平均型的模糊综合评价法,并建立了智能手机评估模型。该模型对手机的各项性能参数进行了分类分析,采用变异系数法计算手机各个评价指标的权重;然后进行单因素评判,建立模糊综合评判矩阵,采用加权平均型算子进行综合评判,得到最后的评估结果。对比实验表明,相对于传统的基于专家赋权和取大取小算法的模糊评价方法,该评估模型的有效性和实用性能均有较大提升,能够更加客观准确地反映用户对智能手机的实际评估。     

一种基于混合多属性的VIKOR群决策方法

针对含有多种属性和混合评价信息群决策问题,提出一种基于直觉模糊VIOKR的评价方法.首先,将不同类型属性值转换为直觉模糊数处理混合评价信息,降低了评价的随机性和模糊性,接着建立最小偏差优化模型计算指标以及专家权重,解决了专家和属性的权重信息未知的问题;引入VIKOR理论集结评价值对评价对象进行评价排序,并与TOPSIS方法进行了对比,说明了本算法的可行性和可信度.最后以某型电源车虚拟训练系统为研究对象,对人员业务水平决策进行实例研究,结果表明该群决策方法能够有效实现决策,具有较好的工程应用价值.     

Evaluating knowledge management capability of organizations: a fuzzy linguistic method

Knowledge management capability (KMC) is the source for organizations to gain the sustainable competitive advantage. KMC evaluation is a required work with strategic significance. However it still has not been addressed in the existing literatures. So the objective of this study is to investigate a fuzzy multiple attributes decision-making method (FMADM) for evaluating KMC. In this paper, a framework for evaluating KMC is presented, which includes two parts, one is an evaluation hierarchy with attributes, the other a judgment matrix model with two dimensions to identify the evaluation results of KMC. Then, a fuzzy linguistic approach is proposed to evaluate the KMC of organizations. The evaluation results of KMC obtained through the proposed approach are objective and unbiased due to two reasons. Firstly, the results are generated by a group of experts in the presence of motile attributes. Secondly, the fuzzy linguistic approach employed in this paper has more advantage to reduce distortion and losing of information than other fuzzy linguistic approaches. Through evaluation result of KMC, managers could judge the necessity to improve the KMC and determine which dimension of KMC is the most needed direction to improve. Additionally, an example is used to illustrate the availability of the proposed method.     

基于神经网络的高校学生信用模糊评价研究

本文为更有效地对高校学生信用进行综合评价,建立了高校学生信用评价多级指标体系,提出了一种基于神经网络的评价模型。模型将模糊理论引入神经网络,通过神经网络的学习训练来调整模糊数学中的相应参数,以有效地模拟模糊综合评价的过程,对信用评价的定性过程而言,具有一定的合理性。     

Agent evaluation based on multi-source heterogeneous information table using TOPSIS

In agent evaluation, a specific role-playing may need more than one capabilities or the task execution process can be divided into several stages. The diverse perspectives to assess candidate agents are denoted as attributes, which is more practical than treating experts as attributes in many other works. In the evaluation table, the attribute values may come from different sources and the data types may not be the same. Therefore, we consider evaluation issues in a Multi-Source Heterogeneous Information System (MSHIS). Considering that grading, voting and marking are three common evaluation scenarios, linguistic variable, Intuitionistic Fuzzy Value (IFV) and real number are utilized to describe the corresponding evaluation results. To evaluate agents in MSHIS, a TOPSIS-based evaluation method is adopted in this work. In the proposed method, the range is utilized to nondimensionalize the distance between agents in each attribute. Then, a weighted Euclidean distance metric is adopted to measure the comprehensive distance. The relative closeness to the ideal agents reflects the agent’s capability on the concerned task. Finally, the illustrative example and comparative experiments are presented to illustrate the effectiveness of our method.     

The agent-based negotiation process for B2C e-commerce

B2C e-commerce is becoming more widespread as more people come to recognize its convenience and its ability to rapidly respond to requests and as more products and services become available. However, many electronic marketplaces, especially in the business-to-consumer, are in essence some kind of search engine where buyers look for the best product in a database of products offered by sellers. Usually, such e-marketplaces do not use agent technology at all although agents could significantly improve the services provided both for the buyers and the sellers. Further, negotiation capabilities are essential for B2C e-commerce systems. In an automated negotiation, intelligent agents engage in broadly similar processes to achieve the same end. In more detail, the agents prepare bids for and evaluate offers on behalf of the parties they represent with the aim of obtaining the maximum benefit for their users. Nevertheless, in the current situation, price is the only criterion by which agents are created. This factor is easy to measure and automate. However, the criteria for advanced transactions need to be elaborated, for example, details of giveback and dividend. In this paper, we present a multiple-attributes negotiation model for B2C e-commerce, which deploys intelligent agents to facilitate autonomous and automatic on-line buying and selling by intelligent agents while quickly responding to consumers. These include a 4-phase model, information collection, search, negotiation, and evaluation. We also apply fuzzy theory and analytical hierarchy process to develop the system interface to facilitate the user inputs. Finally, an example of the notebook purchasing process is illustrated.     

K-means method for rough classification of R&D employees' performance evaluation

This paper proposes an approach that can roughly cluster a data set with fuzzy linguistic entries as a prior data arrangement for performance evaluation of R&D employees. The extension principles of fuzzy linguistic numbers are used to modify the K‐means method for handling the linguistic data set. We define the absolute difference of fuzzy linguistic variables as their fuzzy distance. Based on this definition, the K‐means approach can be modified slightly for clustering purposes. The performance of employees engaged in designing and R&D‐oriented jobs is possibly related to some qualitative attributes and the evaluation of such attributes for each employee has a tendency toward semantic scales. In the proposed approach, the supervisor can evaluate the performance of each employee directly with a semantic scale. The modified K‐means approach can roughly cluster their performance into different classes in advance of applying some other sophisticated processes.     

网管系统的性能模糊综合评价模型

针对网管系统性能评价研究中的度量问题,运用性能指标和模糊数学方法对性能评价进行模糊化处理,以度量的性能数据为基础,采用模糊综合评价方法评价质量因子,通过建立性能综合评价模型,有效地解决了多指标评价问题,可用于指导软件开发人员进行网管系统性能改进。     

基于模糊综合评估的磁浮列车故障诊断系统

阐述了模糊综合评估方法的基本原理,以CMS-3型磁浮列车为研究对象,在PLC硬件平台上建立了列车故障诊断系统的综合评估模型,并分析了系统故障评估模型诊断结论的正确性.CMS-3型磁浮列车故障诊断系统的成功运行,验证了故障综合评估模型能够有效地对系统故障进行诊断.􀁱     

多因素分层模糊综合风险评估方法的应用研究

针对电子档案信息安全指标体系中的指标属性冗余的问题,提出了基于相关分析的指标属性检测方法。该方法采用量化指标属性的原则,根据指标属性的平均值和标准差,度量指标属性间的相关性;针对信息安全风险评估准确度不高的问题,提出了多因素分层模糊综合评估模型,该算法采用了层次分析法和模糊数学理论。某单位的电子档案信息系统的实际应用结果表明,该方法能直观、有效地评估系统,评估结果与实际吻合程度较高,为信息安全风险决策提供可靠的依据。     

一种多维集成直觉模糊信息的信任评价方法

信任是保证在线服务质量的前提。针对电子商务环境存在的复杂性、模糊性和不确定性等因素,引入直觉模糊理论,提出了一种多维集成直觉模糊信息的信任评价方法,给出了两类信任反馈属性集成直觉模糊信息的方法,通过直觉模糊熵确定属性权重,并利用直觉加权算数平均算子求出实体的综合直觉模糊数,从而全面、客观和细腻地反映信任的模糊性和不确定性。计算实例和仿真实验表明,基于多维集成直觉模糊信息的信任评估方法是可行的,通过对风险偏好因子的灵敏度分析,发现服务请求者风险偏好不同,则评估的服务提供商的信任得分也不同;同时也验证了该方法可以有效地抑制恶意节点的攻击,为电子商务环境下信任评价的研究提供了新思路。     

Agent-based diffusion model for an automobile market with fuzzy TOPSIS-based product adoption process

This paper focuses on the product diffusion in a competitive automobile market. Since purchasing a car is costly, the consumers in the market tend to behave like rational decision makers. They naturally compare the attributes of cars (e.g., brand preference, fuel economy, safety, comfort) and make overall decisions. In this paper, we propose an agent-based (AB) diffusion model consisting of tens of thousands of interacting agents. In the model, an agent represents a consumer and bases its multi-attribute decision-making on fuzzy TOPSIS. The decision-making process integrates three purchasing forces: expert’s product information provided by mass media, subjective weights on product attributes assigned by individual consumers, and social influence (i.e., information delivered from a consumer’s neighbors who have already adopted products). The AB model executes the agents and observes the collective behavior. In this sense, the model can assist in the analysis of the complex market dynamics. We conducted an empirical study to verify the performance of the AB model.     

一种基于粗糙2模糊集集成模型的决策分析方法

针对信息系统为连续属性的情况，提出一种将粗糙集与模糊集相结合来获取决策规则的方法，这种基于粗糙—模糊集集成模型求取决策规则的方法通过一个模糊隶属函数将连续属性值表示成模糊值，从而避免了连续属性的离散化问题，同时给出了连续属性值转换成模糊值的表示形式，提出了模糊相似关系和模糊相似类的概念，给出了粗糙—模糊近似空间的下、上近似及其性质以及模糊相似关系下属性约简的方法，最后以自修复飞行控制系统的效能评估为例，给出了自修复效能评估的决策规则。     

Fuzzy quality function deployment: determining the distributions of effort dedicated to technical change

A model is presented that develops the Quality Function Deployment (QFD) House of Quality tool into a fuzzy‐set based multi‐criteria decision‐making process to determine the distributions of effort directed toward technical changes. When customers are polled for desired product‐specific attributes, the responses are typically defined by linguistic variables that represent a fuzzy set distribution. Fuzzy sets also define customer perceptions of the product attributes and technical expert opinions about product design criteria relative to marketplace competitors. Therefore, for each technical criterion, the following factors have an effect on the decision to implement change(s): (1) fuzzy sets providing evidence of customer need for attributes; (2) motivation to change to satisfy desired customer attributes; (3) motivation for technical criterion change; and (4) the strength of the relationships between the attributes and the technical criterion. Priority rankings are linked to the distributions of effort to apply in fulfilling continuous product improvement.     

基于模糊分析的信息系统风险灰色评估模型

为了准确地评价信息系统风险,提出了一种融合模糊层次分析法和灰色评估方法的新模型.从“灰度”概念出发,建立信息系统风险灰色评估模型,消减评价者的主观性.在此基础上引入模糊层次分析法,该方法通过引入模糊数学的有关概念对权重的确定方法进行改进,确保了权重选择的客观性.对信息系统风险的实证进行了研究,实验结果表明了该方法的有效性,为进一步提高信息系统风险评估的准确性提供了可参考的模型和方法支持.