企业培训力评价的模糊综合评判模型

企业培训力是描述企业培训管理体系完备性及其运行有效性的一个集合性概念,它是由多个相关要素构成的模糊集合,具有模糊数学的基本特征。运用模糊数学的基本原理,通过建立模糊综合评判模型以及专家评分法设置二级评价指标体系和相应的权重,对企业培训管理体系的完备性及有效性进行系统、全面的评判,以实现主观向客观、定性向定量的转变,为促进企业培训管理体系的持续改进提供一种科学的思路和方法。     

模糊群决策方法在中间商选择中的应用研究

企业在选择中间商时往往面临着候选伙伴评价指标信息获取的困难,为了使决策科学合理,采用群决策方法集成各领域不同专家的信息,通过语言变量把专家的主观判断转化为对应模糊数,建立相应的数学模型,并计算出用模糊数表示的候选者综合评价值。     

基于FAHP的高技术企业的国际竞争力评价

文章将模糊理论引入到层次分析法中,构建了高技术企业国际竞争力的评价指标体系和决策模型的层次结构,用三角模糊变量表示由专家用自然语言确定的高技术企业的国际竞争力评价准则和各层因素的权重,克服了基于专家的经验和判断的层次分析法中用数字来表示准则和属性的权重的不精确性,利用模糊模拟技术计算被评对象关于评价总目标的权重的期望值,获得较精确的评估结果.     

基于改进BP网络的城市可持续发展水平模糊综合评价

在建立城市可持续发展水平评价指标体系的基础上,提出了一种基于改进BP网络的城市可持续发展水平模糊综合评价方法,该方法不仅可以模拟专家对城市的可持续发展水平进行综合评价,而且有效地改进了人为评价方面的失误,为城市的可持续发展水平评价提供了一种新的评价模型。     

复杂信任网络群组综合评价方法及应用研究

考虑评价环境的复杂不确定性、评价专家的信任行为特征以及群组专家的共识等问题，提出了一种区间Fermatean模糊信任网络群组综合评价方法。首先，针对区间Fermatean模糊评价信息的集成问题，提出了区间Fermatean模糊信息的运算规则，并在此基础上提出了一种区间Fermatean模糊Frank集成方法。其次，考虑到评价专家间信任关系对专家权重和共识达成的影响，构建了基于语言术语的信任网络以计算专家权重，同时设计了个性化反馈机制，进而构建了信任共识交互模型以提高群组共识度。此外，针对评价指标权重未知的情形,提出了区间Fermatean模糊熵权法获取指标权重。最后，通过高校商科类本科生统计设计能力的评价问题验证所提出方法的可行性和优越性。     

基于属性层次分析法的软件外包企业成功度评估分析

本文主要运用属性层次模型,建立我国软件外包企业成功度的评估指标体系,并通过构造属性判断矩阵及赋权得出评估软件外包企业成功度的通用评价模型。在得出评价模型的基础上,利用模糊综合评价模型,通过对业内专家的问卷调查和访谈,最终将定性的评估定量化,得出我国已上市的所有软件外包企业的成功度评估和排位,提出针对性的发展对策和建议。本文创新点在于,运用层次法分析外包企业的地位,对提升企业地位很有裨益。     

基于云模型的跳频无线通信设备抗干扰能力评估方法

评估的置信度是当前无线通信设备抗干扰能力评估工作的瓶颈,其难点在于评估中的模糊性和对主观经验的依赖性。针对该难点,提出了一种基于云模型的跳频无线通信设备抗干扰能力评估方法。首先构造了针对该评估对象的指标体系;其次借用云模型深入分析了评估中的模糊信息及主观因素,并在此基础上提出了置信度计算方法;最后,对算例进行评估和仿真,验证了方法的可行性。该方法主要优势在于既减少了主观成分,提高了评估的科学性和客观性,又较大程度地挖掘了评估中的模糊信息,给出置信度算法,从而反映评估结果的可信性,并为如何提高评估置信度提供了参考方向。     

模糊熵在固有风险评估中的应用探讨

对审计风险实施有效管理的前提是对风险水平的评估,它决定审计工作的成败。针对当前审计实践中主要依靠注册会计师的主观职业判断进行风险评估的现状,必须以固有风险为研究对象,来探讨模糊熵和模糊综合评价法在固有风险评估的应用,以缩小主观判断和实际水平之间的差异,更有效地保证审计质量和审计效率的提高。     

装备制造业知识管理创新能力多层次模糊综合测评

将集成AHP(Analytic Hierarchy Process)和多层次模糊分析的方法,应用于装备制造业知识管理创新能力的综合评价,建立了测评指标权重集,避免确定权重的主观片面性,建立了多层次模糊评价模型。实验表明多层次模糊综合测评分析法不仅适用于装备制造业知识管理创新能力的综合评价,对制造业知识创新的相关规范的制定和综合评价指标体系的完善具有一定的指导意义。     

介绍一种从人员评估到人员开发的方法

一个企业的兴衰,很大程度上取决于这个企业员工素质以及由此而采用的管理模式。为克服传统人员素质评估方法的缺陷,介绍了一种把人员素质评估与人员开发相结合起来的教学方法：先用多层次模糊综合评判模型对人员素质进行评估,然后将评估的结果引入所建立的人员价值系数模型中,据以确定人员的开发方案,并进一步对组织进行开发。     

The Development of a Process for Evaluating Marketing Sponsorships

Despite the increasing resources being allocated from marketing budgets to sponsorship, effective evaluation is relatively rare, and sponsorship evaluation methods are often proprietary in nature. This paper reports on a research project designed to develop a process model for evaluating sponsorships. An initial version was conceived from agency theory, the evaluation literature, and sponsorship writings. This draft was then assessed by sponsorship experts during a series of 14 in‐depth interviews. Based on these analyses, a final version of the process model was proposed. The revised version was then adopted to evaluate—as a demonstrative example—a specific sponsorship. Results of this case and recommendations for future research and practice in sponsorship evaluation are presented. Copyright © 2011 ASAC. Published by John Wiley & Sons, Ltd.     

Multiple Attribute Group Decision-Making Methods with Completely Unknown Weights in Intuitionistic Fuzzy Setting and Interval-Valued Intuitionistic Fuzzy Setting

The existing multiple attribute group decision-making approaches based on intuitionistic fuzzy sets (IFSs) or interval-valued intuitionistic fuzzy sets (IVIFSs) are considered as the situation that the weights of experts are given beforehand and the attribute weights are known or unknown. To better describe the uncertain decision environment and solve the corresponding decision problem, multiple attribute group decision-making methods with completely unknown weights of both experts and attributes are proposed in intuitionistic fuzzy setting and interval-valued intuitionistic fuzzy setting. Entropy weight models can be used to determine the weights of both experts and attributes from intuitionistic fuzzy decision matrices or interval-valued intuitionistic fuzzy decision matrices, and then the evaluation formulas of weighted correlation coefficients between alternatives and the ideal alternative are introduced in intuitionistic fuzzy setting and interval-valued intuitionistic fuzzy setting. The alternatives can be ranked and the most desirable one(s) can be selected according to the values of the weighted correlation coefficients for IFSs or IVIFSs. Finally, two numerical examples demonstrate the effectiveness of the proposed methods: they are capable for handling the multiple attribute group decision-making problems with completely unknown weights.     

改进BP神经网络在企业网络营销绩效评价中的应用

在研究网络营销本质及其绩效特征的基础上,建立企业网络营销绩效评价指标体系并采用BP神经网络建立评价模型。为了克服传统BP神经网络容易陷入局部极小、收敛速度慢的缺点,通过采用LM算法和学习速率的自适应调整来建立新型的BP神经网络,利用模糊综合评价法生成训练样本。该评价模型有效地利用了BP神经网络的优点,避免了评价过程的人为失误。仿真试验表明,该模型取得了较好的效果。     

A Fuzzy Multi-Criteria Decision Making Model for IS Student Group Project Assessment

To accommodate the criterion-referenced student group project assessment approach, this paper proposes a fuzzy group Multi-Criteria Decision Making (MCDM) model. The proposed model can be used to solve student group project assessment problem in particular and generic MCDM problems in general, where the criteria used are often different and can be scored with multiple preference formats. The proposed fuzzy group MCDM model supports seven different preference formats, including preference ordering, utility vector, linguistic term vector, selected subset, fuzzy selected subset, fuzzy preference relation, and normal preference relation. It has been firstly used in the context of Information Systems (IS) student group project assessment.     

Uncertain Power Average Operators for Aggregating Interval Fuzzy Preference Relations

In this paper, we investigate group decision making problems based on interval fuzzy preference relations. We define an uncertain power weighted average (UPWA) operator and an uncertain power ordered weighted average (UPOWA) operator, on the basis of the power average operator of Yager (IEEE Trans Syst Man Cybern A 31:724–731, 1988) and the uncertain geometric mean. In the situations where the weights of experts are known, we develop a method based on the UPWA operator for group decision making with interval fuzzy preference relations; and in the situations where the weights of experts are unknown, we develop a method based on the UPOWA operator for group decision making with interval fuzzy preference relations.     

模糊数学在人力资源管理绩效评价中的应用研究

随着全球经济一体化进程的加快,企业与企业之间的竞争越来越表现为人才的竞争。人力资源的开发与管理在企业管理中的地位尤为显得重要,那么如何引导和积极地推进人力资源的开发与管理工作呢?其中很重要的一环是人力资源管理绩效的综合评价。研究人力资源管理评价指标,探讨模糊数学在人力资源管理评价中的应用,构建人力资源管理模糊综合评价模型,为加强公司人力资源管理提供了依据。     

学生水平的模糊综合评价模型

针对学生水平评价问题,提出一种模糊综合评价模型,模型综合考虑多种评价因素及其权值,以模糊数学为工具,利用模糊变换和模糊合成等运算实现学生水平的判断,进而更准确的了解学生学习情况,并给予切实的指导.     

Fuzzy Development of Multiple Response Optimization

This paper proposes a developed approach to Multiple Response Optimization (MRO) in two categories; responses without replicates and with some replicates based on fuzzy concepts. At first, the problem without any replicate in responses is investigated, and a fuzzy Decision Support System (DSS) is proposed based on Fuzzy Inference System (FIS) for MRO. The proposed methodology provides a fuzzy approach considering uncertainty in decision making environment. After calculating desirability of each response, total desirability of each experiment is measured by using values of each response desirability, applying membership function and fuzzy rules expressed by experts. Then Response Surface Methodology (RSM) is applied to fit a regression model between total desirability and controllable factors and optimize them. Next, a methodology is proposed for MRO with some replicates in responses which optimizes mean and variance simultaneously by applying fuzzy concepts. After introducing Deviation function based on robustness concept and using desirability function, a two objective problem is constituted. At last, a fuzzy programming is expressed to solve the problem applying degree of satisfaction from each objective. Then the problem is converted to a single objective model with the goals of increasing desirability and robustness simultaneously. The obtained optimum factor levels are fuzzy numbers so that a bigger satisfactory region could be provided. Finally, two numerical examples are expressed to illustrate the proposed methodologies for multiple responses without replicates and with some replicates.     

模糊多级综合评判在煤炭资源资产评估中的应用

矿产资源的评估不仅是地质人员的工作,而且也是采矿、矿山测量和经济管理人员的研究课题。影响煤炭资源资产评估的因素有地质因素、采矿因素、社会因素及经济因素。根据这些影响因素在煤炭资源资产评估中的影响程度,设立了评估指示体系,并引入模糊多级综合评判理论,建立了煤炭资源资产综合评判模型,并进行了实例研究和模型检验。     

A safe speed guidance model for highways

ABSTRACT

This paper presents a fuzzy logic model to support decisions for the suggested speed limit for sections of highways as they become affected by adverse road conditions, environmental factors and differing traffic levels. The definition of the main factors, and their weight, that reduce safety on highways was conducted by the Delphi method, consulting traffic engineering experts. The survey served as a basis for structuring indicators and indexes in a soft decision tree, structured by a fuzzy logic system. The system can be used to support the decisions of those that manage the roads, indicating to drivers’ speeds, by visual, audible or combined systems.