云决策分析方法

提出一种基于不确定性人工智能的决策分析方法.该方法利用云理论中的云变换和概念提升方法来刻画属性因素的概念云模型,并对每个因素都分配相应的云权重;使用X-条件云和极大判定法,找出每个因素的最佳评判语言云模型;让云权重参与综合评判,最终通过云计算得到基于云滴分布的综合评价结果.实验结果表明,与传统的模糊决策分析相比,它更具有易理解性,广普适性和高准确性等特点.

     

云数据中心及云平台技术运用

云计算是一种基于互联网的计算方式,而云(计算)数据中心实现了云计算基础架构的解决方案,其融合了安全策略、并行计算、能源管理、自动化及虚拟化等技术,目前在电信、电力、广电、金融及互联网等领域得以广泛应用.据此,本文笔者首先介绍云平台的关键技术,然后再进一步探讨云数据中心的建设.     

基于PDCA模型的云资源管理方法研究

随着云计算技术的发展,企业级的云计算平台在数字化浪潮中占据越来越重要的地位。云资源管理是云平台运行的关键环节,要在确保云平台稳定运行的基础上提升云资源利用效率,目前大多数企业级平台已经历大规模建设阶段,在使用阶段暴露出闲置资源多、资源分配不均、缺少管理要求及统一规范等问题,故亟需构建一套科学的云资源管理方法论,实现云资源精益管理。在PDCA模型的基础上,提出了云资源管理方法,拓展管理者对云资源全过程管理的视野,挖掘痛点问题,为企业级云计算平台长效化管理提供参考。     

云成本分析

云计算已经成为现今互联网发展的主题,其延伸和发展出的云存储也当仁不让地成为了主流的数据存储和管理方式。那么,经营一个云端的成本和收益到底如何呢?文中将以Backblaze等公司的云成本和收益情况进行分析。     

不能忽略云模式,亦要对云有效管理

对于公司来说,云模式不应该被忽略;与此同时,针对云的特点进行有效管理也属于必须要做的工作。现在,公司开展工作的重点就变成了对管理需求进行全面分析,确保可以通过云服务模式得以实现。在进行战略规划时,这属于首先要考虑的关键问题。     

可信云——云时代的新生态

云计算已成为信息通信领域最具活力的增长点之一.云服务改变了以往的信息化模式,正引领软件、硬件和网络技术的深度融合与快速创新,深刻地影响着整个信息通信产业的发展格局.2013年10月,可信云服务认证正式启动,这标志着我国也拥有了自己的云服务质量评估体系.可信云服务认证的核心目标是建立云服务商的评估体系,为用户选择安全、可信的云服务商提供支撑,并最终促进我国云计算市场健康、有序发展.     

大数据时代的云存储技术

随着大数据时代的来临,以及云计算技术的迅猛发展,作为信息时代的全新产品云存储也成为存储领域的新宠,云存储改变了以往数据主要集中在本地存储和处理的传统模式,企业和个人用户无需再投入大量购置硬件等设施的成本,就能够方便快捷地通过网络根据需求访问计算与存储等服务。本文从云存储的概念、云存储的分类、云存储的优势、云存储需要考虑的问题等方面来介绍一下云存储技术。     

云测试综述

针对云计算的定义及云计算的特点做出分析。认为云计算有着良好的发展趋势,并在次基础上展开对云测试的讨论,主要涉及云测试的特点、优点、应用现状,云测试平台以及云测试技术,并探讨云测试的对现有测试服务模式的影响及存在的缺陷,预测云测试的发展趋势。     

云测试综述

针对云计算的定义及云计算的特点做出分析。认为云计算有着良好的发展趋势,并在次基础上展开对云测试的讨论。主要涉及云测试的特点、优点、应用现状,云测试平台以及云测试技术,并探讨云测试的对现有测试服务模式的影响及存在的缺陷,预测云测试的发展趋势。     

基于云理论与神经网络集成的模糊系统

提出了一种基于云理论与神经网络混合集成的模糊系统。通过不确定性人工智能,解决了在实际模糊系统中输入变量隶属函数和知识规则确定的难题,利用神经网络实现了变量之间的非线性映射。该系统不但具有神经网络自适应的学习能力,且结合云理论处理知识的不确定性能力,使模糊系统在知识推理过程中更具有说服力,在整体上提高了算法的效率。     

基于云计算的数据挖掘技术研究

目前,网络中利用数据挖掘技术抽取有效信息成为数据挖掘研究的热点。介绍数据挖掘的流程和分类,并对在云端进行数据的收集和储存提出自己的思想。重点对数据收集的网格和分形维数的聚类算法(GFDC),以及在网络频繁的数据迁移中处理好Master和服务器之间的关系进行了改进。     

浅析云计算安全技术

在互联网技术高速发展的今天,云计算已成为热门技术。在云计算中,一切资源放在云端,故云安全问题显得尤为突出。介绍了云计算概念,阐述了云计算面临的安全挑战,并从技术层面提出解决云安全的防范措施,打造一个用户放心的云计算安全平台。     

Composite decision support by combining cost-benefit and multi-criteria decision analysis

This paper concerns composite decision support based on combining cost-benefit analysis (CBA) with multi-criteria decision analysis (MCDA) for the assessment of economic as well as strategic impacts within transport projects. Specifically a composite model for assessment (COSIMA) is presented as a decision support system (DSS). This COSIMA DSS ensures that the assessment is conducted in a systematic, transparent and explicit way. The modelling principles presented are illuminated with a case study concerning a complex decision problem. The outcome demonstrates the approach as a valuable DSS, and it is concluded that appraisals of large transport projects can be effectively supported using a combination of CBA and MCDA. Finally, perspectives of the future modelling work are given.     

Study of decision implications based on formal concept analysis

In this paper, the notions of decision table and decision rule in Rough Set Theory are introduced naturally into Formal Concept Analysis as decision context and decision implication. Since extracting decision implications directly from decision context takes time, we present an inference rule called α-decision inference rule to eliminate the superfluous decision implications. Moreover, based on the inference rule we introduce the notion of α-maximal decision implication and prove that the set of all α-maximal decision implications is complete (α-complete) and non-redundant (α-non-redundant). Finally, we present a method to generate the set.     

基于行为均衡分析的多学科协同决策机制设计

针对求解不确定、动态和分布式的多学科设计优化问题时所面临的挑战,提出了一种基于行为均衡分析的多学科协同决策机制。在行为博弈分析框架下,通过采用折衷决策支持问题建立学科设计团队的基本决策模型,利用理性反应集刻画团队之间的交互作用和耦合关系,结合社会偏好理论、认知演算和前景理论来描述团队之间行为均衡的实现过程,该机制为多学科设计博弈的动态演化过程提供了一个有效的建模工具。     

Fuzzy rule based decision trees

This paper presents a new architecture of a fuzzy decision tree based on fuzzy rules – fuzzy rule based decision tree (FRDT) and provides a learning algorithm. In contrast with “traditional” axis-parallel decision trees in which only a single feature (variable) is taken into account at each node, the node of the proposed decision trees involves a fuzzy rule which involves multiple features. Fuzzy rules are employed to produce leaves of high purity. Using multiple features for a node helps us minimize the size of the trees. The growth of the FRDT is realized by expanding an additional node composed of a mixture of data coming from different classes, which is the only non-leaf node of each layer. This gives rise to a new geometric structure endowed with linguistic terms which are quite different from the “traditional” oblique decision trees endowed with hyperplanes as decision functions. A series of numeric studies are reported using data coming from UCI machine learning data sets. The comparison is carried out with regard to “traditional” decision trees such as C4.5, LADtree, BFTree, SimpleCart, and NBTree. The results of statistical tests have shown that the proposed FRDT exhibits the best performance in terms of both accuracy and the size of the produced trees.     

探析云计算中的信息安全

阐述了云计算的基本概念、特点及其工作原理,并在此基础上深入探讨和研究了由云计算带来的信息安全问题以及其相应的解决问题的措施。     

集对云多属性群决策方法及应用

阐明了复杂现象模糊多属性决策方法的研究现状,并针对复杂现象语言调研信息存在的主观模糊性与客观随机性以及不确定性因素对决策备选方案的影响等问题,结合云模型与集对分析的相关理论和方法,研究设计了集对云多属性群决策方法。将该方法用于我国"农村新能源开发利用规划"研究中,建立了可再生能源开发决策模型,给出了相应的解法。与模糊二元语义分析法进行的比对实验说明了集对云决策法的合理性、有效性及实用性。     

Fuzzy aggregation operators in decision making with Dempster-Shafer belief structure

We study the decision-making problem with Dempster-Shafer theory of evidence. We analyze how to deal with this model when the available information is uncertain and it can be represented with fuzzy numbers. We use different types of aggregation operators that aggregate fuzzy numbers such as the fuzzy weighted average (FWA), the fuzzy ordered weighted averaging (FOWA) operator and the fuzzy hybrid averaging (FHA) operator. As a result, we get the belief structure fuzzy weighted average (BS-FWA), the belief structure fuzzy ordered weighted averaging (BS-FOWA) operator and the belief structure fuzzy hybrid averaging (BS-FHA) operator. We further generalize this new approach by using generalized and quasi-arithmetic means. We also develop an illustrative example regarding the selection of investments where we can see the different results obtained by using different types of fuzzy aggregation operators.     

A method using weight restrictions in data envelopment analysis for ranking and validity issues in decision making

In this article we introduce a comprehensive yet efficient approach based on data envelopment analysis (DEA) with restricted multipliers for accountable and understandable multiple attribute decision making (MADM). Information system (IS) appraisals are motivated and used for illustrating the proposed methodology. Results show that the given DEA based approach can easily and significantly increase the information frame of the decision maker by identifying disparate rankings and by affirming the stability and validity of ranking outcomes. The given validity concept is contrary to the directions given in the main body of research and can also be used to question ranking outcomes of classic MADM methods.