基于Vague集的航空装备研制过程决策方法研究

针对航空装备研制过程决策问题,分析了现有Vague集进行多准则模糊决策的现有记分函数,建立了新的计分函数,提出了基于Vague集的航空装备研制过程决策方法,为航空装备研制过程的控制提供了一种有效的方法.     

基于区间直觉模糊记分函数的动态专利质量评价方法

记分函数是对区间直觉模糊集进行比较和集结的重要工具，其排序能力直接影响评价结果的优劣。本文在总结整理现行的区间直觉模糊集记分函数的基础上，从直觉符合性和能否描述决策者模糊判断两个层面，系统分析了现有记分函数的不足。并在此基础上，引入集对分析方法构建改进的区间直觉模糊集记分函数，并证明了其相关性质。根据提出的记分函数，本文设计区间直觉模糊型动态群决策方法，并将其应用于专利质量评价中。     

面向直觉模糊集排序能力提升的记分函数设计研究

直觉模糊集记分函数的排序能力是影响直觉模糊型多准则决策绩效的重要因素。本文以直觉模糊集记分函数的特性分析为切入点,较为系统地分析了现有各类记分函数的有界性、符合直觉性、排序能力、连续性等四类特征;其次,基于现有记分函数特征匹配状况,提出了新的直觉模糊集记分函数的分段函数并加以证明;最后,系统比较了现有记分函数与本文提出的记分函数在排序能力和区分度方面的差异,验证了本方法的优越性和合理性。     

基于Vague集的模糊多目标决策方法及应用

针对目前基于Vague集多目标决策中Vague值计算困难以及确定目标满意度的下界和不满意度的上界存在主观随意性问题.提出了一种基于Vague集的模糊多目标决策方法.利用属性数学中的属性集和属性测度理论构造目标的真隶属度函数、假隶属度函数和犹豫度函数,从而可计算出目标的Vague值;采用记分函数计算方案的多目标评分值,从而可以对方案进行排序并选择出最优方案.应用实例验证了该方法的有效性和实用性.     

基于Vague集的TOPSIS

针对应用广泛的TOPS IS方法的特征,研究在V ague集中应用TOPS IS的方法.首先用记分函数来确定理想解和负理想解,在此基础上建立了基于V ague集的TOPS IS的决策方法,并通过实际算例验证了此方法的有效性.     

基于Vague集思想的电子产品可靠性评价

针对电子产品可靠性评价中存在的问题,将Vague集理论引入到评价环节.通过指标选取、权重确定、Vague加权集结、记分函数计算等四个环节的计算,剔除了可靠性评价中的不确定性信息.方法体现了Vague集理论描述不确定性问题的优点,反映了电子产品可靠性评价的一般特点,得到了公平公正的评价结果,方法的应用具有一定推广价值.     

基于记分函数的语言型多准则决策方法

分析了语言指标的特点,提出语言指标与Vague值转换的基本思路,给出语言指标与典型Vague值的转换方法.该方法能够保持决策者风险偏好的一致性.证明了在各方案属性的语言指标转化为Vague值后,即使采用不同风险偏好的记分函数,也能得到相同的记分值范围,据此提出基于记分函数的语言型多准则决策方法.通过实例说明该方法能减少决策者的风险偏好对决策结果的影响,提高决策的客观性和准确性.     

基于证据理论和Vague集的多属性群决策方法研究

为了解决人们在复杂环境中决策困难的问题,论文基于Vague集描述不确定事物的优势,通过证据理论对Vague集进行合成,得到一种信息集结的多属性群决策方法。该算法首先考虑专家评分的可信度,在分析Vague集与证据理论的数学关系后,使用证据理论将各方案在各属性下的专家集证据集结。然后通过Vague集记分函数进行属性权重的计算,将方案集在属性集下的Vague评价值进行加权修正,再通过证据理论将属性集证据集结得到各方案最终的Vague评价值。之后使用记分函数计算每一方案的得分来确定最优方案。最后通过算例进一步说明所提方法的可行性与有效性。文章给出的算法使决策者在不确定环境下可以进行理性决策,从而选出最优方案。     

基于灰色聚类-SPA的建筑施工项目安全风险评价

针对建筑施工阶段的安全风险,建立了基于灰色聚类-集对分析(SPA)的建筑施工项目安全风险的综合评价模型.在应用SPA确定安全风险评价因素权重的基础上,采用灰色聚类方法对建筑施工项目进行聚类分析,评价建筑施工项目安全风险所处的等级,最后依据SPA中集对势等级次序表分析建筑施工项目安全风险发展态势.实例分析证明了该模型的适用性和合理性,对比分析表明其评价结果的可靠性,为施工企业的安全风险决策提供借鉴.     

基于改进犹豫模糊熵的群体MULTMOORA决策方法

针对既有犹豫模糊元记分函数的存在的不足,引入记分系数,提出考虑决策者风险态度的犹豫模糊记分函数,并验证其相关性质.同时,对于现有犹豫模糊熵定义具有的缺陷,提出基于模糊熵的犹豫模糊熵的新定义,并给出相应的犹豫模糊熵公式.在以犹豫模糊元为输入信息的复杂统框架内,提出基于改进犹豫模糊熵的MULTIMOORA群体决策方法,并将其应用于物流供应商选择中.案例分析表明了此方法的可行性及有效性.     

A online credit evaluation method based on AHP and SPA

Online credit evaluation is the foundation for the establishment of trust and for the management of risk between buyers and sellers in e-commerce. In this paper, a new credit evaluation method based on the analytic hierarchy process (AHP) and the set pair analysis (SPA) is presented to determine the credibility of the electronic commerce participants. It solves some of the drawbacks found in classical credit evaluation methods and broadens the scope of current approaches. Both qualitative and quantitative indicators are considered in the proposed method, then a overall credit score is achieved from the optimal perspective. In the end, a case analysis of China Garment Network is provided for illustrative purposes.     

Smoothed perturbation analysis algorithms for estimating the derivatives of occupancy-related functions in serial queueing networks

We present unbiased Smoothed Perturbation Analysis (SPA) estimators for the derivatives of occupancy-related performance functions in serial networks ofG/G/1 queues with respect to parameters of the distributions of service times at the queues. The sample functions for these performance measures are piecewise constant, and established Infinitesimal Perturbation Analysis (IPA) methods typically fail to provide unbiased estimators in this case. The performance measures considered in this paper are: the average network occupancy as seen by an arrival, the average occupancy of a specific queue as seen by an arrival to it, the probability that a customer is blocked at a specific queue, and the probability that a customer leaves a queue idle. The SPA estimators derived are quite simple and flexible, and they lend themselves to straightforward analysis. Unlike most of the established SPA algorithms, ours are not based on the comparison of hazard rates, and the proofs of their unbiasedness do not require the boundedness of such hazard rates.Supported in part by the National Science Foundation under Grant ECS-8801912, by the Office of Naval Research under Contract N00014-87-K-0304, and by NASA under Contract NAG 2-595.     

一般罚分(或得分)矩阵下的SPA算法

本文在一般罚分（或得分）矩阵条件下推广SPA（Super Pairwise Alignment）算法，该算法是一种次优算法，与Smith-Waterman算法比较，计算速度有明显改进（计算复杂度随序列长度线性增长）．     

基于集对论的居民消费研究

基于集对分析方法和近20年来的居民消费数据,建立了我国城镇居民的消费增量预测模型、进而研究了居民的消费水平。通过和常规的回归方法相比,阐明了集对分析方法在研究居民消费增量的等级变化问题方面的优点。研究结果也表明了集对分析方法在等级分类和趋势预测这一类似确定又不确定的问题上有良好的应用效果。     

网络体系结构建模和性能评价的形式化方法——随机进程代数

随机进程代数是从经典进程代数发展起来 ,用于并发系统的定性和定量分析的形式化方法 ,特别适合在计算机网络和通信协议的建模和性能评价 .首先介绍了 SPA的语法和操作语义 .并以令牌环局域网模型为例来说明其应用 .进一步讨论了 SPA的三种等价关系 ,以期解决模型状态空间爆炸问题 .     

基于SPA的双枝模糊决策分析

将集对理论(SPA)与双枝模糊决策理论相结合,用集对分析的方法研究进行双枝模糊决策的方法,分别对双枝模糊决策因素域和双枝模糊决策的上枝、下枝和双枝进行了集对分析,给出了用SPA进行双枝模糊决策的性质,同时讨论了双枝模糊决策的动态分析方法,以及双枝模糊决策度强弱态势预测的方法,从而为双枝模糊决策理论的研究提供了新的视角和方法,为双枝模糊决策的应用提供了更方便的工具和更强的理论支持。     

区间直觉模糊集多属性决策方法

定义了区间直觉模糊集的加权算子和加权几何集成算子,介绍了现有的区间直觉模糊集的得分函数和精确函数.定义了一个新的精确函数,此函数弥补了已有函数的不足和缺陷,应用新定义的精确函数,提出了对区间直觉模糊集多属性决策问题进行决策的方法.最后以应用实例对该方法进行说明和验证.     

Predicting ships' CO2 emissions using feature‐oriented methods

Shipping companies are forced by the current EU regulation to set up a system for monitoring, reporting, and verification of harmful emissions from their fleet. In this regulatory background, data collected from onboard sensors can be utilized to assess the ship's operating conditions and quantify its CO₂ emission levels. The standard approach for analyzing such data sets is based on summarizing the measurements obtained during a given voyage by the average value. However, this compression step may lead to significant information loss since most variables present a dynamic profile that is not well approximated by the average value only. Therefore, in this work, we test two feature‐oriented methods that are able to extract additional features, namely, profile‐driven features (PdF) and statistical pattern analysis (SPA). A real data set from a Ro‐Pax ship is then considered to test the selected methods. The data set is segregated according to the voyage distance into short, medium, and long routes. Both PdF and SPA are compared with the standard approach, and the results demonstrate the benefits of employing more systematic and informative feature‐oriented methods. For the short route, no method is able to predict CO₂ emissions in a satisfactory way, whereas for the medium and long routes, regression models built using features obtained from both PdF and SPA improve their prediction performance. In particular, for the long route, the standard approach failed to provide reasonably good predictions.     

A profile-type smoothed score function for a varying coefficient partially linear model

The varying coefficient partially linear model is considered in this paper. When the plug-in estimators of coefficient functions are used, the resulting smoothing score function becomes biased due to the slow convergence rate of nonparametric estimations. To reduce the bias of the resulting smoothing score function, a profile-type smoothed score function is proposed to draw inferences on the parameters of interest without using the quasi-likelihood framework, the least favorable curve, a higher order kernel or under-smoothing. The resulting profile-type statistic is still asymptotically Chi-squared under some regularity conditions. The results are then used to construct confidence regions for the parameters of interest. A simulation study is carried out to assess the performance of the proposed method and to compare it with the profile least-squares method. A real dataset is analyzed for illustration.