Modified Computational Ranking Model for Cloud Trust Factor Using Fuzzy Logic

Through the use of the internet and cloud computing,users may access their data as well as the programmes they have installed.It is now more challenging than ever before to choose which cloud service providers to take advantage of.When it comes to the dependability of the cloud infrastructure service,those who supply cloud services,as well as those who seek cloud services,have an equal responsibility to exercise utmost care.Because of this,further caution is required to ensure that the appropriate values are reached in light of the ever-increasing need for correct decision-making.The purpose of this study is to provide an updated computational ranking approach for decision-making in an environment with many criteria by using fuzzy logic in the context of a public cloud scenario.This improved computational ranking system is also sometimes referred to as the improvised VlseKriterijumska Optimizacija I Kompromisno Resenje(VIKOR)method.It gives users access to a trustworthy assortment of cloud services that fit their needs.The activity that is part of the suggested technique has been broken down into nine discrete parts for your convenience.To verify these stages,a numerical example has been evaluated for each of the six different scenarios,and the outcomes have been simulated.

New Ranking of Generalized Quadrilateral Shape Fuzzy Number Using Centroid Technique

The output of the fuzzy set is reduced by one for the defuzzification procedure.It is employed to provide a comprehensible outcome from a fuzzy inference process.This page provides further information about the defuzzifica-tion approach for quadrilateral fuzzy numbers,which may be used to convert them into discrete values.Defuzzification demonstrates how useful fuzzy ranking systems can be.Our major purpose is to develop a new ranking method for gen-eralized quadrilateral fuzzy numbers.The primary objective of the research is to provide a novel approach to the accurate evaluation of various kinds of fuzzy inte-gers.Fuzzy ranking properties are examined.Using the counterexamples of Lee and Chen demonstrates the fallacy of the ranking technique.So,a new approach has been developed for dealing with fuzzy risk analysis,risk management,indus-trial engineering and optimization,medicine,and artificial intelligence problems:the generalized quadrilateral form fuzzy number utilizing centroid methodology.As you can see,the aforementioned scenarios are all amenable to the solution pro-vided by the generalized quadrilateral shape fuzzy number utilizing centroid methodology.It’s laid out in a straightforward manner that’s easy to grasp for everyone.The rating method is explained in detail,along with numerical exam-ples to illustrate it.Last but not least,stability evaluations clarify why the Gener-alized quadrilateral shape fuzzy number obtained by the centroid methodology outperforms other ranking methods.

A New Fuzzy Clustering-Ranking Algorithm and Its Application in Process Alarm Management

Overmany alarms of modern chemical process give the operators many difficulties to decision and diag- nosis. In order to ensure safe production and process operating, management and optimization of alarm information are challenge work that must be confronted. A new process alarm management method based on fuzzy clustering- ranking algorithm is proposed. The fuzzy clustering algorithm is used to cluster rationally the process variables, and difference driving decision algorithm ranks different clusters and process parameters in every cluster. The alarm signal of higher rank is handled preferentially to manage effectively alarms and avoid blind operation. The validity of proposed algorithm and solution is verified by the practical application of ethylene cracking furnace system. It is an effective and dependable alarm management method to improve operating safety in industrial process.

New Decision-Making Technique Based on Hurwicz Criteria for Fuzzy Ranking

Efficient decision-making remains an open challenge in the research community,and many researchers are working to improve accuracy through the use of various computational techniques.In this case,the fuzzification and defuzzification processes can be very useful.Defuzzification is an effective process to get a single number from the output of a fuzzy set.Considering defuzzification as a center point of this research paper,to analyze and understand the effect of different types of vehicles according to their performance.In this paper,the multi-criteria decision-making(MCDM)process under uncertainty and defuzzification is discussed by using the center of the area(COA)or centroidmethod.Further,to find the best solution,Hurwicz criteria are used on the defuzzified data.Anewdecision-making technique is proposed using Hurwicz criteria for triangular and trapezoidal fuzzy numbers.The proposed technique considers all types of decision makers’perspectives such as optimistic,neutral,and pessimistic which is crucial in solving decisionmaking problems.A simple case study is used to demonstrate and discuss the Centroid Method and Hurwicz Criteria for measuring risk attitudes among decision-makers.The significance of the proposed defuzzification method is demonstrated by comparing it to previous defuzzification procedures with its application.

Rank Functions of Fuzzy Greedoids

Fuzzy greedoids were recently introduced as a fuzzy set generalization of (crisp) greedoids. We characterize fuzzy languages which define fuzzy greedoids, give necessary properties and sufficient properties of the fuzzy rank function of a fuzzy greedoid, give a characterization of the rank function for a weighted greedoid, and discuss the rank closure of a fuzzy greedoid.

A Review on Ranking of Z-numbers

There are numerous studies about Z-numbers since its inception in 2011.Because Z-number concept reflects human ability to make rational decisions,Z-number based multi-criteria decision making problems are one of these studies.When the problem is translated from linguistic information into Z-number domain,the important question occurs that which Z-number should be selected.To answer this question,several ranking methods have been proposed.To compare the performances of these methods,benchmark set of fuzzy Z-numbers has been created in time.There are relatively new methods that their performances are not examined yet on this benchmark problem.In this paper,we worked on these studies which are relative entropy based Z-number ranking method and a method for ranking discrete Z-numbers.The authors tried to examine their performances on the benchmark problem and compared the results with the other ranking algorithms.The results are consistent with the literature,mostly.The advantages and the drawbacks of the methods are presented which can be useful for the researchers who are interested in this area.

乘型模糊判断矩阵排序向量的递推方法

文章首先在模糊判断矩阵乘型一致性以及矩阵元素和权重之间关系的基础上,结合模糊判断矩阵的上三角矩阵元素,构建了一个关于权重和矩阵上三角元素的方程组,并证明了该方程组存在唯一的正解。随后指出方程组的证明过程就是模糊判断矩阵排序向量的求解过程,从而给出了乘型一致性模糊判断矩阵排序向量的一种递推方法。然后,在偏差函数基础上,通过构造并求解一个优化模型,求出了非乘型一致性模糊判断矩阵的排序向量,结果显示,其解的形式与采用乘型一致性模糊判断矩阵递推方法得到的排序向量完全一样。最后,通过实例以及相关方法对比说明排序向量递推方法是可行有效的。

基于Fuzzy偏好关系的一种方案排序方法

如何根据Ｆｕｚｚｙ 偏好关系选择最优方案或进行方案的排序是一个重要的研究内容·针对Ｆｕｚｚｙ 偏好关系提出了一种新的方案排序方法·首先描述了Ｆｕｚｚｙ 偏好关系及其含义， 然后建立了一个最优化模型并通过求解该模型来得到方案的参考排序值， 使最终方案的排序结果最大程度地反映决策者的偏好， 最后给出了一个算例·

带有Fuzzy偏好关系的多属性决策方法

针对多属性决策分析中决策者给出关于方案的Fuzzy偏好关系 ,提出了一种新的多属性决策方法·该方法是通过建立一个线性目标规划模型来确定属性的权重向量并相应地进行方案的排序 ,得到的方案排序结果体现了决策者给出的方案偏好信息与决策矩阵的集成 ,并最大程度地反映了决策者的偏好·最后给出了一个算例·

Fuzzy标准矩阵及Fuzzy强标准矩阵

本文在格L=[0,1]上定义了Fuzzy标准矩阵及Fuzzy强标准矩阵,得出了他们的一些基本性质。证明了Fuzzy标准矩阵是幂收敛阵;给出了Fuzzy强标准矩阵的判别条件及Fuzzy强标准矩阵是幂等的充要条件。最后对Fuzzy强标准矩阵的秩进行了讨论。

Fuzzy拟阵的子结构

本文给出了3种不同的Fuzzy拟阵的子结构,对子结构M(?),讨论了它的秩函数,基,圈,σ算子等性质.

基于模糊集和RSS的Web教育资源Rank算法

随着Web教育资源指数级增长以及受污染程度的加剧,如何汇聚异构网络环境下面向用户的Web教育资源成为新的挑战。为了使终端用户能够获得高效有序的Web教育资源,文中提出了一种基于模糊集和RSS的Web教育资源Rank算法,并进行了相关分析。算法首先通过模糊集中的Euclid模糊度刻画查询内容与资源之间的模糊关联度;其次采用RSS聚合技术快速汇聚用户需要的Web教育资源;最后基于中国知网数据集的实验表明,该算法能满足Web教育资源终端用户个性化资源获取的需要。

L-Fuzzy正则矩阵与可逆矩阵的秩

L表示有最小元 (记为 0 )与最大元 (记为 1 )的分配格 ,对于L上的矩阵给出了保持Schein秩不变的前提下的一种化简方法 ,并给出矩阵的Schein秩为 1的条件 .对于L上的正则矩阵 ,证明了它的行秩、列秩与Schein秩三者相等 ;对于L上的可逆方阵 ,证明了它是满秩的 .

设施农业雨水集蓄利用方案综合评价方法研究

本研究为设施农业雨水高效集蓄利用方案设计提供理论依据,也为其他高效节水农业评价和筛选提供参考。综合考虑经济成本、技术性能、运行管理和环境影响等四方面因素,构建设施农业雨水集蓄利用方案的评价指标体系;采用改进的秩相关分析和AHP模糊综合评价(Reelies-AHP-FSE)模型,结合专家评分和序列关系法对设施农业雨水高效集蓄利用影响因子进行定量分析;通过模糊综合评价进行雨水传输系统、蓄水系统两种系统方案的打分,比选研究区设施农业雨水集蓄利用最优方案。结果表明:矩形混凝土沟+整坡处理的模糊综合指标值为3.922,为雨水传输过程技术中的优选方案;管道式蓄水结构的模糊综合评价值为4.003,为雨水蓄水方案中的最优选项。该评价方法从地形适应、蓄水效果、水质维护等方面进行了材料和形式优选,对于推广设施农业雨水集蓄利用具有借鉴意义。

Fuzzy矩阵Schein秩的求法

本文给出了Fuzzy矩阵Schein秩的一种较理想的求法,最后得到了Fuzzy矩阵Schein秩的一个下界表示.

有限Fuzzy关系方程与Fuzzy矩阵秩进一步研究

在［１］的基础上，讨论了一般有限Ｆｕｚｚｙ 关系方程极小解的结构；将［１］中特殊有限Ｆｕｚｚｙ 关系方程与矩阵秩的关系推广到一般有限Ｆｕｚｚｙ 关系方程，运用矩阵秩给出了有限Ｆｕｚｚｙ关系方程极小解个数的上界估计，同时给出了求一般有限Ｆｕｚｚｙ 关系方程全部极小解一种全新算法．

基于模糊一致性调整算法的推荐系统评估研究

考虑到一致性调整和排序权重向量确定方法是犹豫模糊语言群决策中的2个重要课题,构造基于一致性调整算法的犹豫模糊语言群决策模型。具体来说,该模型首先运用对数最小二乘法计算犹豫模糊语言偏好关系(hesitant fuzzy linguistic preference relation,HFLPR)的排序权重向量;其次,将一致性指数最小的语言偏好关系对应的排序权重向量作为HFLPR的序权重向量;随后,基于一致性调整算法建立了一种收敛的犹豫模糊语言群决策模型。该模型既没有改变原始犹豫模糊语言术语集,又可以尽可能地避免信息的损失;最后,将建立的模型应用于推荐系统的优选过程。实验表明,构建的群决策算法更合理有效。

Fuzzy矩阵的秩

许多学者对Fuzzy矩阵的秩进行了研究,但在Fuzzy矩阵的秩与积、和运算的关系方面,探讨还很不够.本文在格L=[0,1]上利用已有的一些结论得到了Fuzzy矩阵秩的一些重要性质,并讨论了Fuzzy有限生成子空间的秩与Fuzzy矩阵秩的关系.最后指出一个错误.

Fuzzy矩阵的Schein秩与Fuzzy不定方程

本文在格 L=[0,1]上讨论了 Fuzzy 矩阵不定方程的指数,可实现矩阵的容度及 Fuzzy 矩阵的行(列)秩(Schein 秩)之间的关系,给出了非零 Fuzzy 矩阵不定方程有解的几个判别定理,证明了 n×m级 Fuzzy 矩阵 A 的 Schein 秩等于 min{n,m}的几个充分条件.

加权可靠性FCOM算法的苗族服饰图像分割

针对苗族服饰图像存在保存不清晰、折痕、污渍沾染的问题,提出一种加权可靠性模糊C有序均值聚类算法。首先,将排序技术、损失函数和像素数据的典型性结合起来,对数据样本点可靠性进行分析,保证算法的鲁棒性与稳健性。其次,引入一组加权超参数,简化算法的复杂度,提高算法的灵活性。最后,引入新的隶属度约束函数,构造新的目标函数,对数据项进行更加强制清晰的划分。实验结果表明该算法在模糊划分系数、模糊划分熵及Xie-Beni系数等方面均优于其他几种FCM算法。