针对传统计划评审技术(Program Evaluation and Review Technique,PERT)在计算完工概率时假设条件的局限性(假设条件与工程实际存在偏差,导致完工概率偏大),提出了基于贝叶斯网络的施工进度完工概率分析方法.首先,分析了贝叶斯网络与进...针对传统计划评审技术(Program Evaluation and Review Technique,PERT)在计算完工概率时假设条件的局限性(假设条件与工程实际存在偏差,导致完工概率偏大),提出了基于贝叶斯网络的施工进度完工概率分析方法.首先,分析了贝叶斯网络与进度计划网络之间的相似性,将两者结合起来构建了贝叶斯进度网络;在此基础上,综合考虑贝叶斯网络在节点取值及概率计算方面的优越性,并结合工程项目的不确定性及复杂性特点,建立了基于贝叶斯网络的施工进度完工概率分析模型.最后,将该模型应用于具体工程进行实例分析,验证了模型的可行性与有效性.研究结果表明:基于贝叶斯网络的进度完工概率模型充分考虑了工程施工中的风险因素,其结果能更客观地反映工程实际,可为工程项目决策者提供可靠的依据.展开更多
In cloud computing(CC),resources are allocated and offered to the cli-ents transparently in an on-demand way.Failures can happen in CC environment and the cloud resources are adaptable tofluctuations in the performance...In cloud computing(CC),resources are allocated and offered to the cli-ents transparently in an on-demand way.Failures can happen in CC environment and the cloud resources are adaptable tofluctuations in the performance delivery.Task execution failure becomes common in the CC environment.Therefore,fault-tolerant scheduling techniques in CC environment are essential for handling performance differences,resourcefluxes,and failures.Recently,several intelli-gent scheduling approaches have been developed for scheduling tasks in CC with no consideration of fault tolerant characteristics.With this motivation,this study focuses on the design of Gorilla Troops Optimizer Based Fault Tolerant Aware Scheduling Scheme(GTO-FTASS)in CC environment.The proposed GTO-FTASS model aims to schedule the tasks and allocate resources by considering fault tolerance into account.The GTO-FTASS algorithm is based on the social intelligence nature of gorilla troops.Besides,the GTO-FTASS model derives afitness function involving two parameters such as expected time of completion(ETC)and failure probability of executing a task.In addition,the presented fault detector can trace the failed tasks or VMs and then schedule heal submodule in sequence with a remedial or retrieval scheduling model.The experimental vali-dation of the GTO-FTASS model has been performed and the results are inspected under several aspects.Extensive comparative analysis reported the better outcomes of the GTO-FTASS model over the recent approaches.展开更多
As from time to time it is impractical to ask agents to provide linear orders over all alternatives,for these partial rankings it is necessary to conduct preference completion.Specifically,the personalized preference ...As from time to time it is impractical to ask agents to provide linear orders over all alternatives,for these partial rankings it is necessary to conduct preference completion.Specifically,the personalized preference of each agent over all the alternatives can be estimated with partial rankings from neighboring agents over subsets of alternatives.However,since the agents’rankings are nondeterministic,where they may provide rankings with noise,it is necessary and important to conduct the certainty-based preference completion.Hence,in this paper firstly,for alternative pairs with the obtained ranking set,a bijection has been built from the ranking space to the preference space,and the certainty and conflict of alternative pairs have been evaluated with a well-built statistical measurement Probability-Certainty Density Function on subjective probability,respectively.Then,a certainty-based voting algorithm based on certainty and conflict has been taken to conduct the certainty-based preference completion.Moreover,the properties of the proposed certainty and conflict have been studied empirically,and the proposed approach on certainty-based preference completion for partial rankings has been experimentally validated compared to state-of-arts approaches with several datasets.展开更多
文摘针对传统计划评审技术(Program Evaluation and Review Technique,PERT)在计算完工概率时假设条件的局限性(假设条件与工程实际存在偏差,导致完工概率偏大),提出了基于贝叶斯网络的施工进度完工概率分析方法.首先,分析了贝叶斯网络与进度计划网络之间的相似性,将两者结合起来构建了贝叶斯进度网络;在此基础上,综合考虑贝叶斯网络在节点取值及概率计算方面的优越性,并结合工程项目的不确定性及复杂性特点,建立了基于贝叶斯网络的施工进度完工概率分析模型.最后,将该模型应用于具体工程进行实例分析,验证了模型的可行性与有效性.研究结果表明:基于贝叶斯网络的进度完工概率模型充分考虑了工程施工中的风险因素,其结果能更客观地反映工程实际,可为工程项目决策者提供可靠的依据.
文摘In cloud computing(CC),resources are allocated and offered to the cli-ents transparently in an on-demand way.Failures can happen in CC environment and the cloud resources are adaptable tofluctuations in the performance delivery.Task execution failure becomes common in the CC environment.Therefore,fault-tolerant scheduling techniques in CC environment are essential for handling performance differences,resourcefluxes,and failures.Recently,several intelli-gent scheduling approaches have been developed for scheduling tasks in CC with no consideration of fault tolerant characteristics.With this motivation,this study focuses on the design of Gorilla Troops Optimizer Based Fault Tolerant Aware Scheduling Scheme(GTO-FTASS)in CC environment.The proposed GTO-FTASS model aims to schedule the tasks and allocate resources by considering fault tolerance into account.The GTO-FTASS algorithm is based on the social intelligence nature of gorilla troops.Besides,the GTO-FTASS model derives afitness function involving two parameters such as expected time of completion(ETC)and failure probability of executing a task.In addition,the presented fault detector can trace the failed tasks or VMs and then schedule heal submodule in sequence with a remedial or retrieval scheduling model.The experimental vali-dation of the GTO-FTASS model has been performed and the results are inspected under several aspects.Extensive comparative analysis reported the better outcomes of the GTO-FTASS model over the recent approaches.
基金supported by the National Natural Science Foundation of China(No.62076087,No.61906059&No.62120106008)the Program for Changjiang Scholars and Innovative Research Team in University(PCSIRT)of the Ministry of Education of China under grant IRT17R32
文摘As from time to time it is impractical to ask agents to provide linear orders over all alternatives,for these partial rankings it is necessary to conduct preference completion.Specifically,the personalized preference of each agent over all the alternatives can be estimated with partial rankings from neighboring agents over subsets of alternatives.However,since the agents’rankings are nondeterministic,where they may provide rankings with noise,it is necessary and important to conduct the certainty-based preference completion.Hence,in this paper firstly,for alternative pairs with the obtained ranking set,a bijection has been built from the ranking space to the preference space,and the certainty and conflict of alternative pairs have been evaluated with a well-built statistical measurement Probability-Certainty Density Function on subjective probability,respectively.Then,a certainty-based voting algorithm based on certainty and conflict has been taken to conduct the certainty-based preference completion.Moreover,the properties of the proposed certainty and conflict have been studied empirically,and the proposed approach on certainty-based preference completion for partial rankings has been experimentally validated compared to state-of-arts approaches with several datasets.
