识表示中的不确定性

知识表示一直是人工智能研究中的一个瓶颈,其难点在于知识中隐含有不确定性,即模糊性和随机性.文章提出用云模型3个数字特征(期望值,熵,超熵)来描述一个定性概念,用熵来关联模糊性和随机性.代表定性概念的云的某一次定量值,被称为云滴,可以用它对此概念的贡献度来衡量,许许多多云滴构成云,实现定性和定量之间的随时转换,反映了知识表示中的不确定性.论文以此对我国农历24个节气进行了新的量化解释.云方法已经用于数据开采、智能控制、跳频电台和大系统效能评估中,取得明显的效果.     

知识表示中的不确定性

知识表示一直是人工智能研究中的一个瓶颈,其难点在于知识中隐含有不确定性,即模糊性和随机性。意提出用云模型3个数字特征（期望值,熵,超熵）来描述一个定性概念,用熵来关联模糊性和随机性。代表定性概念的云的某一次定量值,被称为云滴,要以用它对此概念的贡献度来衡量,许许多多云滴构成云,实现实性和定量之间的随时转换,反映了知识表示中的不确定性。论以此对我国农历24个节气进行了新的最化解释。云方法已经用于数据开采、智能控制、跳频电台和大系统效能评估中,取得明显的效果。     

非对称网络信任模型研究

信任能够解决网络实体间的安全问题。根据实体的行为变化,在实体间建立信任关系能够有效防护恶意实体的攻击。研究非对称信任模型,并且提出域内信任模型和域间信任模型。为准确地判断实体间的信任关系,提出实体信任值的评估算法及其更新函数。最后,研究非对称信任模型的工作流程,并且分析实体交易后的信任值,这种判断方法能够保证恶意实体所带来的损失降到最低。     

用于分布式系统的安全模型

提出一个用于分布式系统的基于信任的安全模型,该模型具有信任模块,授权模块,交互模块,以及效用计算模块,这四个模块相互作用和配合,成为一个高效的评估系统。分析表明与没有风险控制的现有信任模型相比,该系统能更加及时准确地对节点可信度进行评估,从而有效地减少分布式系统中恶意节点对系统的伤害,同时使系统效用最大化。     

基于贝叶斯网络的组合服务信任度评估方法

对组合服务信任度评估问题进行了研究。基于信任的不确定性和模糊性,给出了信任度的离散化表示方法;借助于贝叶斯网络的强大的推理能力,给出了组合服务的贝叶斯网络模型以及组合服务模型到贝叶斯网络的转换规则,利用贝叶斯网络的正向推理机制设计了基于贝叶斯网络模型的组合服务信任度评估方法。通过一个组合服务的买例,说明了组合服务的贝叶斯网络模型及其基于贝叶斯网络的组合服务信任度评估方法的使用方法。该评估方法基于信任的模糊性和不确定性,更符合信任的本质并易于实现。     

基于云重心评判的应急柴油机启动状态评估方法

应急柴油机(EDG)是保证核电厂安全可靠运行的一级安全设备,其应急启动成功率是衡量核电站安全等级的关键指标之一,因此对E D G启动过程进行有效监测评估具有重要价值。本文利用在线监测系统采集EDG启动过程数据,考虑瞬变启动数据的不确定性,提出了一种基于云重心模型的EDG启动状态评估方法。首先,充分结合EDG快速启动特点,选择能够反映E D G启动阶段缸内发火做功和高压空气做功状态的7个特征参数作为评估指标,为准确计算特征指标,提出了适用于快速启动过程的瞬时转速优化计算方法和振动信号角域精确重采样方法。然后,利用云模型在解决随机性和不确定性问题方面的优势,构建综合云评估模型,将云重心评判法引入到EDG启动状态评估中。最后,以实际核电现场多次测试数据为分析案例,利用本文提出的特征提取方法和综合云评估模型对测量状态进行评估,验证了所提方法的有效性,为EDG启动状态评估提供了有效途径。     

P2P网络中基于实体行为的分布式信任模型

对Peer—to-Peer网络环境下实体信任模型进行了研究,提出了一个通用的基于用户行为的分布式信任模型。该模型通过量化实体行为和计算实体信任度来评估实体间的信任关系。模型引入了修正因子和评价准确度反馈系统,有效地提高了模型的准确性。     

基于云模型的爆破振动影响度评估研究

针对爆破振动危害效应的影响因素众多,且各因素之间的综合作用具有不确定性的特点,基于云模型理论,建立了爆破振动对建筑物影响度的云模型评估模型。选取峰值振速、主振频率、持续时间、建筑物结构类型、建筑物新旧程度、场地条件6个主要影响因素作为评估指标,计算各指标隶属于不同爆破振动影响程度等级的云模型数字特征,结合正向正态云模型和指标权重,计算待评估对象的综合确定度,最后确定爆破振动影响度等级,将该方法应用于贵州省花安高速某边坡爆破振动对周边民房的影响度评估中。研究结果表明:云模型评估结果与模糊可拓分析法的评估结果较一致,且符合爆后实际调查情况,为合理评估爆破振动危害影响提供了一种新思路。     

论正态云模型的普适性

分布函数是分析随机现象的重要工具，正态分布是最重要的概率分布，在自然科学和社会科学中应用广泛；隶属函数是模糊集合的基石，正态隶属函数也有广泛的应用。但是，精确确定一个模糊概念的隶属函数已经成为模糊学应用的瓶颈。云模型把随机性和模糊性结合起来，用数字特征熵，揭示随机性与模糊性的关联性，并用来表示一个定性概念的粒度。正态云模型通过期望、熵和超熵构成的特定结构发生器，生成定性概念的定量转换值，体现概念的不确定性。这种特定结构不但放宽了形成正态分布的前提条件，而且把精确确定隶属函数放宽到构造正态隶属度分布的期望函数，因而更具有普遍适用性，更简单、直接地完成了定性与定量之间的相互转换过程。     

基于综合信任的奇异值分解推荐算法研究

针对传统矩阵分解推荐算法中数据稀疏、冷启动和用户信任矩阵数据稀疏等问题,本文提出了一种改进的基于路径的信任计算模型,利用用户-用户之间的直接信任关系和受信任者对用户信任关系的影响,计算用户-用户之间存在的间接信任关系,从而填充用户-用户信任矩阵。在此基础上,将用户之间的信任关系与奇异值分解(SVD)模型相结合,提出了一种融合综合信任的奇异值分解算法,即CT-SVD算法。该推荐算法结合用户评分矩阵和信任关系矩阵,对传统的奇异值分解推荐算法进行优化,提高了推荐系统评分预测的准确性。在FilmTrust和Ciao数据集上的实验结果表明,该算法能够有效地缓解推荐系统的数据稀疏性和冷启动问题。     

Research on Trust Model in Container-Based Cloud Service

Container virtual technology aims to provide program independence and resource sharing. The container enables flexible cloud service. Compared with traditional virtualization, traditional virtual machines have difficulty in resource and expense requirements. The container technology has the advantages of smaller size, faster migration, lower resource overhead, and higher utilization. Within container-based cloud environment, services can adopt multi-target nodes. This paper reports research results to improve the traditional trust model with consideration of cooperation effects. Cooperation trust means that in a container-based cloud environment, services can be divided into multiple containers for different container nodes. When multiple target nodes work for one service at the same time, these nodes are in a cooperation state. When multi-target nodes cooperate to complete the service, the target nodes evaluate each other. The calculation of cooperation trust evaluation is used to update the degree of comprehensive trust. Experimental simulation results show that the cooperation trust evaluation can help solving the trust problem in the container-based cloud environment and can improve the success rate of following cooperation.     

A Multi-Tenant Usage Access Model for Cloud Computing

Most cloud services are built with multi-tenancy which enables data and configuration segregation upon shared infrastructures. It offers tremendous advantages for enterprises and service providers. It is anticipated that this situation will evolve to foster cross-tenant collaboration supported by Authorization as a service. To realize access control in a multi-tenant cloud computing environment, this study proposes a multi-tenant cloud computing access control model based on the traditional usage access control model by building trust relations among tenants. The model consists of three submodels, which achieve trust relationships between tenants with different granularities and satisfy the requirements of different application scenarios. With an established trust relation in MT-UCON (Multi-tenant Usage Access Control), the trustee can precisely authorize cross-tenant accesses to the trustor’s resources consistent with constraints over the trust relation and other components designated by the trustor. In addition, the security of the model is analyzed by an information flow method. The model adapts to the characteristics of a dynamic and open multi-tenant cloud computing environment and achieves fine-grained access control within and between tenants.     

基于熵权-云模型的印品质量评价模型

目的目前各种印刷质量评价模型均有一定的局限性,提出一种新的印品评价模型,以有效准确地判断印品的质量。方法利用熵权法解决参数之间的平衡性问题,确定5个参数的加权分别为0.2,0.25,0.2,0.17,0.19,同时参照ISO印刷标准,确定最终的印刷品正态评价集,选取5个基本印刷参数进行云模型的计算。结果 5种样品的印品质量评价最大隶属度分别为0.7800,0.7038,0.7257,0.6105,0.3870,由此得出印刷品的五级制等级分别为优、中、中、优和优,用于衡量印刷品的质量。结论运用熵权法加权后的云模型充分考虑印刷品评价的主观性与客观性的统一,评价出印品质量的等级更加客观有效,与topsis方法的结论保持一致,说明了模型的有效性和准确性,同时云模型更利用分析印刷机械的印刷特征,为印刷操作人员提供相应的理论指导。     

三级倒立摆的云控制方法及动平衡模式

文章提出了定性和定量之间转换的云模型的形式化表示方法,用来反映语言值中蕴涵的模糊性和随机性,给出云发生器的生成算法,解释多条定性推理规则同时被激活时的不确定性推理机制。利用这种智能控制方法有效地实现了单电机控制的一、二、三级倒立摆的多种不同动平衡姿态,显示其鲁棒性,并给出了详细试验结果。研究成果不仅可用于对太空飞行器以及机器人控制,而且对揭示定性定量转换规律和策略具有普遍意义。     

Mobile Internet Mobile Agent System Dynamic Trust Model for Cloud Computing

In mobile cloud computing, trust is a very important parameter in mobile cloud computing security because data storage and data processing are performed remotely in the cloud. Aiming at the security and trust management of mobile agent system in mobile cloud computing environment, the Human Trust Mechanism (HTM) is used to study the subjective trust formation, trust propagation and trust evolution law, and the subjective trust dynamic management algorithm (MASTM) is proposed. Based on the interaction experience between the mobile agent and the execution host and the third-party recommendation information to collect the basic trust data, the public trust host selection algorithm is given. The isolated malicious host algorithm and the integrated trust degree calculation algorithm realize the function of selecting the trusted cluster and isolating the malicious host, so as to enhance the security interaction between the mobile agent and the host. Given algorithm simulation and verification were carried out to prove its feasibility and effectiveness.     

Performance computation methods for composition of tasks with multiple patterns in cloud manufacturing

Task composition in cloud manufacturing involves the selection of appropriate services from the cloud manufacturing platform and combining them to process the task with the purpose of achieving its expected performance. Calculation methods for achieving the performance expected by customers when the task has two or more composition patterns (e.g. sequential and switching pattern) are necessary because most tasks have multiple composition patterns in cloud manufacturing. Previous studies, however, have focused only on a single composition pattern. In this paper, we regard a task as a directed acyclic graph, and propose graph-based algorithms to obtain cost, execution time, quality and reliability of a task having multiple composition patterns. In addition, we model the task composition problem by introducing cost and execution time as performance attributes, and quality and reliability as basic attributes in the Kano model. Finally, an experiment to compare the performances of three metaheuristic algorithms (namely, variable neighbourhood search, genetic, and simulated annealing) is conducted to solve the problem. The experimental result shows that the variable neighbourhood search algorithm yields better and more stable solutions than the genetic algorithm and simulated annealing algorithms.