警务绩效的模糊综合评价方法研究

警务绩效评估有利于强化警察机构的组织管理,提高警察的工作效能。针对警务绩效的综合评价问题,制定了警务绩效评估原则,建立了多因素、多层次的警务绩效评价指标体系,并基于模糊数学的评判理论,提出对警务绩效进行整体评价的多级模糊综合评价方法,最后通过一个应用实例,验证了该方法的有效性和实用性。     

警务绩效评估系统的UML建模及实现

警务绩效评估有利于强化警察机构的组织管理,提高警察的工作效能。提出了基于金盾网的警务绩效评估系统结构,采用面向对象的分析与设计方法,使用统一建模语言UML对系统建模,详细分析和设计了系统的用例图、静态结构模型和动态行为模型,描述了系统采用的多级模糊综合评价方法,最后使用ASP.NET技术实现了该系统。     

模糊数学对招募专员绩效评估的应用

主要介绍招募系统中模糊数学综合评价方法对招募专员绩效评估的应用。在算例中,首先人事经理给出招募专员的绩效考核方法,然后建立模糊综合评价模型,最后运用该模型对招募专员绩效进行科学、客观的评价。模糊数学理论为招募专员绩效评估提供一种方法。     

面向软件交付的绩效评估系统应用研究

针对软件交付过程中绩效考核不规范的问题,根据给定的软件交付过程模型,利用关键绩效指标的考核体系,设计了绩效评估系统,给出了关键指标和相应权重的选取和设定过程。系统根据给出的各个阶段的指标体系和权重,应用模糊综合评价的方法,对各个阶段各个指标的评价成绩和总成绩进行绩效评估,实现了对软件项目的量化管理。最后分析了系统的应用对软件项目的影响。     

警务信息化风险识别与评价模型研究

本文分析了警务信息化风险的类型,设计了警务信息化项目风险评价的指标体系,最后采用基于模糊理论的方法设计了警务信息化风险评价的计算模型。     

电子政务项目后评价指标体系初探

电子政务项目后评价是电子政务绩效评估体系的有机组成部分。本文概述了电子政务项目后评价工作的目的、意义,在此基础上,对电子政务项目后评价工作的实施及其评价指标体系的建立进行了初步研究和探讨,提出三级电子政务项目后评价指标体系框架,并给出了指标权重的确定方法。本文的内容对深入研究和构建适合我国国情的电子政务绩效评估体系有一定的借鉴意义。     

虚拟学习社区的绩效评估模型

基于虚拟学习社区的特点,综合社区学习者学习积极性、知识水平和能力水平三个方面来对学习社区绩效进行评估。针对目前网络学习评价大多仅限于对在线测验成绩进行评价的不足,充分利用综合评判带来的信息,结合社区协作学习和自主学习的特点,建立了一个社区学习绩效模糊综合评价模型。为了解决模型评价结果为隶属向量,模糊度较大和最大隶属原则有可能导致评价结果失真的问题,重点提出并建立隶属等级量化精确模型对评价向量作进一步量化,进一步准确区分学生,并与初等量化方法作了比较分析。     

浅析电脑统计学与社区警务

现代警务是与现代经济社会和法律制度相适应的一种新型警务,而信息系统是当今警察机构的核心电路系统,通常能决定问题的定义和过程的评估。社区警务的变革,以及类似电脑统计学等警务新方法包含了复杂信息技术的发展。在社区警务运动进行之前,信息技术被广泛运用于高科技行业,与警务部门的日常运作相分离。信息技术已经在扮演着一个更新,更重要的角色。     

基于灰色理论的上市公司经营绩效综合评价探究

本文在研究上市公司经营绩效影响因素的基础上,建立了上市公司经营绩效评价指标体系,的数学评价模型,并结合实例利用多层次灰色评价理论对上市公司经营绩效进行了有效的综合评价,验证了该方法的可操作性,希望为上市公司改善经营绩效提供一定的参考价值。     

基于模糊德尔菲法的高职电子信息技术专业实训基地的评价法

应用模糊德尔菲法对高职电子信息技术专业实训基地进行有效的绩效评估,该评价法是基于模糊综合评价法建立的评价指标体系,通过德尔菲法建立评价指标权重系数,然后在此基础评价专业实训基地的指标。     

多层次模糊综合评判法在教师教学工作业绩评价中的应用

教师教学工作业绩评价是高校教学评估环节中的一项重要工作,但教师业绩在评价过程中不可避免地存在大量的模糊性等不确定性因素,为了更客观、公正、恰当地给出相应的评价,以便促进教师业务水平的提升,给出一种改进型的模糊综合评判方法,建立基于层次分析法的教师业绩综合评价模型,利用AHP方法确定评价指标的权重,利用加权平均法计算评判的数据。算例结果表明,基于多层次的模糊综合评判教师业绩可以得到良好的评价结果。     

基于改进DS理论的双重模糊信息安全评估

针对信息安全评估的模糊性,考虑之前算法的单一方面模糊问题,分析信息安全系统不同时间段内的表现,提出一种基于改进DS理论的双重模糊信息安全评估算法。不仅利用三角模糊数方法把专家观点进行聚合,还用改进的DS理论充分体现出不同时间段内系统的表现会造成的对专家评价结果的影响,根据风险计算公式,最终得到威胁严重程度排序。与单一决策算法相比,综合考虑了信息安全系统的不确定性和主观人为的不确定性,避免了单一时间段内的笼统决定,通过实验,验证了该方法的必需性及有效性。     

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。     

The evaluation of financial performance for Taiwan container shipping companies by fuzzy TOPSIS

In this paper, financial performance of Taiwan container shipping companies are evaluated by fuzzy multi-criteria decision-making (FMCDM). In the evaluating problem, we first apply grey relation analysis to partition financial ratios into several clusters and find representative indices from the clusters. Then the representative indices are considered as evaluation criteria on financial performance assessment of Taiwan container shipping companies, and an FMCDM method called fuzzy technique for order preference by similarity to ideal solution (fuzzy TOPSIS) is utilized to evaluate financial performance. By fuzzy TOPSIS, financial performances of container shipping companies are ranked, and thus a container shipping company can realize its finance competitive strength and weakness between container shipping companies.     

An integrated fuzzy synthetic evaluation approach for supplier selection based on analytic network process

In order to ensure the uninterrupted supply of items, the suppliers’ performance needs to be evaluated periodically. The evaluation process typically consists of identifying the attributes and criteria relevant to the decision, and measuring the performance of a supplier by considering the relevant criteria. But the evaluation process is complex. Linguistic assessment of suppliers may be carried out based on several criteria. Much of the data are difficult to obtain and ambiguous or vague to interpret. Nonetheless, a rational process of evaluation must exist to select the most appropriate suppliers. This paper develops a supplier evaluation approach based on the analytic network process (ANP) and fuzzy synthetic evaluation under a fuzzy environment. The importance weights of various criteria are considered as linguistic variables. These linguistic ratings can be expressed in triangular fuzzy numbers by using the fuzzy extent analysis. Fuzzy synthetic evaluation is used to select a supplier alternative and the Fuzzy ANP (FANP) method is applied to calculate the importance of the criteria weights. Then an integrated FANP and fuzzy synthetic evaluation methodology is proposed for evaluating and selecting the most suitable suppliers. A hypothetical example is presented and the results indicated that the combination of ANP and fuzzy synthetic evaluation provided useful tool to select the optimal supplier.     

Mobile formative assessment tool based on data mining techniques for supporting web-based learning

Current trends clearly indicate that online learning has become an important learning mode. However, no effective assessment mechanism for learning performance yet exists for e-learning systems. Learning performance assessment aims to evaluate what learners learned during the learning process. Traditional summative evaluation only considers final learning outcomes, without concerning the learning processes of learners. With the evolution of learning technology, the use of learning portfolios in a web-based learning environment can be beneficially adopted to record the procedure of the learning, which evaluates the learning performances of learners and produces feedback information to learners in ways that enhance their learning. Accordingly, this study presents a mobile formative assessment tool using data mining, which involves six computational intelligence theories, i.e. statistic correlation analysis, fuzzy clustering analysis, grey relational analysis, K-means clustering, fuzzy association rule mining and fuzzy inference, in order to identify the key formative assessment rules according to the web-based learning portfolios of an individual learner for the performance promotion of web-based learning. Restated, the proposed method can help teachers to precisely assess the learning performance of individual learner utilizing only the learning portfolios in a web-based learning environment. Hence, teachers can devote themselves to teaching and designing courseware, since they save a lot of time in measuring learning performance. More importantly, teachers can understand the main factors influencing learning performance in a web-based learning environment based on the interpretable learning performance assessment rules obtained. Experimental results indicate that the evaluation results of the proposed scheme are very close to those of summative assessment results and the factor analysis provides simple and clear learning performance assessment rules. Furthermore, the proposed learning feedback with formative assessment can clearly promote the learning performances and interests of learners.     

Novel methodologies and a comparative study for manufacturing systems performance evaluations

The purpose of this work is to establish complex fuzzy methodologies in the evaluation of a manufacturing system’s performance. Many empirical studies have been presented about the evaluation of manufacturing system’s performance. However, the performance evaluation is quite subjective, since it relies on the individual judgment of the managers who have different, various and multi-factor assessment methods of a system’s performance. In this study, two fuzzy modeling designs were developed and in the construction of the models, a hierarchy process was used. In the first method, the performance factors and the Analytic Hierarchy Process (AHP) were fuzzified and the use of fuzzy numbers and a fuzzy AHP for this problem was recommended. Also, the relative importance of these factors with respect to each other and their contribution to the overall performance was quantified with fuzzy linguistic terms. In the other method, we proposed Approximate Reasoning (AR) based on experts’ knowledge which is represented with the collection of the rules. These fuzzy rule bases are “if-then” linguistic rules that are formed with linguistic variables such as poor, below average, average, above average and superior. Additionally, the problem was structured with the normal AHP and System-With-Feedback (SWF), Finally, these methods were compared. The results showed that fuzzy AHP leads to the best result. It is expected that the recommended models would have an advantage in the competitive manufacturing including cost, flexibility, quality, speed and dependability.     

基于模糊攻防树和熵权法的工控系统脆弱性量化评估方法

为了提高脆弱性量化评估结果的可靠性,提出一种基于模糊攻防树和熵权法的工控系统脆弱性量化评估方法。该方法以攻击防御树为模型,首先将模糊集合理论与专家评价相结合,然后聚合多位专家对同一安全属模糊评价,在模糊聚合过程中利用模糊距离计算专家模糊评价的偏离度以提高模糊聚合的可靠性,并采用熵权法确定叶子节点量化过程中各安全属性的权重。最后计算叶子节点及攻击序列概率。案例分析表明,该方法能有效提高评估结果的可靠性,为工控系统信息安全防护提供重要依据。