基于本体扩展的软件构件原型系统的设计

在构件检索中引入本体,结合刻面分类信息和领域信息,建立起软构件本体模型,提出了基于本体的软构件语义检索的推理模式及算法,对用户提交的查询请求进行有效的语义扩展和推理,提高构件的检索效率,同时为分布、异构构件库的准确、全面、方便的构件检索提供了帮助。     

基于领域本体的构件自动化组装原形系统

介绍了领域本体的概念，分析了构件自动化组装的阶段和方面，给出了一个基于领域本体的自动化构件组装原型系统（ontology based automated assembly system，OBAAS），介绍了系统整体框架，并对该系统的基于领域本体的构件分类引擎，构件检索匹配和构件接口匹配验证模块的实现思想进行了详细说明，给出了利用朴素贝叶斯分类方法在领域本体基础上对构件的分类的算法、基于领域本体的构件检索和匹配算法，以及部分数据结构的描述。     

Fault detection and identification based on combining logic and model in a wall-climbing robot

A combined logic- and model-based approach to fault detection and identification （FDI） in a suction foot control system of a wall-climbing robot is presented in this paper. For the control system, some fault models are derived by kinematics analysis. Moreover, the logic relations of the system states are known in advance. First, a fault tree is used to analyze the system by evaluating the basic events （elementary causes）, which can lead to a root event （a particular fault）. Then, a multiple-model adaptive estimation algorithm is used to detect and identify the model-known faults. Finally, based on the system states of the robot and the results of the estimation, the model-unknown faults are also identified using logical reasoning. Experiments show that the proposed approach based on the combination of logical reasoning and model estimating is efficient in the FDI of the robot.     

构件组装及其形式化推导研究

基于构件的软件工程(component based software engineering,简称CBSE)能够有效地提高软件开发的质量和效率.构件组装和组装推导(compositional reasoning)是CBSE的关键技术.基于软件构件的特点,借鉴进程代数中进程构造的方法,提出6种构件组装机制,能够灵活、简便地集成软件构件,并主张在构件组装的同时进行接口组装,通过生成功能更强、抽象级别更高的复合接口,提高构件组装的抽象级别和粒度.同时,基于Wright的形式化规约软件体系结构的研究,给出了复合构件和复合接口的组装推导算法,为系统行为的形式化分析、验证和仿真奠定了基础.     

一个支持构件库动态演变的构件检索系统

在基于构件的软件开发CBD(component－based Software development)中,随着可重用构件库的不断增长,构件的分类和检索技术一直是软件重用组织十分关注的问题.文章提出了一个支持构件库动态演变的构件检索系统;为了改进该系统的检索性能,还采用了多种构件检索方法.     

形式化方法对构件库管理系统支持的探讨

依据网上信息收集系统构件库中构件的开发和管理经验,提出一种构件模型,并阐述了此模型对基于语义的构件检索构件组装和构件演化的自动化支持     

可重构路由交换平台中的构件分类检索方法

针对可重构路由交换平台构件库中构件检索效率不高的现状,提出一种基于刻面的软硬件构件分类方法。基于该方法设计误差反向传播神经网络构件检索算法,分析表明该算法具有并行性强、效率高、速度快的特点,适合规模大、构成复杂的构件库检索问题。仿真结果证明,在构件数量较多的情况下,该算法性能优于传统检索算法。     

J2EE平台下的PLM构件库系统的设计与实现

软件构件库作为软件复用的一项重要基础设施,得到了产业界和学术界越来越多的重视。文中结合PLM项目背景,提出了一种在J2EE平台下的PLM构件库系统（PLMCLS）的设计和实现方案。给出了PLMCLS的整体框架,并用UML用例图说明该构件库管理系统包括的功能。PLMCLS把PLM构件整体上分为九个层次的构件,对各个层次上构件进行刻面描述并提供接口描述信息,在检索和匹配机制采用语义检索和语法匹配的模式,保证了构件的重用率并为快速掏建PLM系统提供了有效支持。     

基于Agent的分布式构件库系统体系结构

在分析了构件库及其复用现状的基础上,引入Agent技术,提出了一个基于Agent的分布式构件库系统,给出了体系结构.该系统通过多Agent之间的相互协作,能较好地满足在各企业间跨越构件库请求并检索构件的需求.     

一种可扩展的构件库数据模型

在基于构件的软件开发（CBSD）中，构件库是描述、存储和检索软件构件的基础设施。随着软件复用技术的成熟，构件库中构件的种类日益增多，构件间关系日渐复杂。这需要构件库数据模型提供相应的支持。为了给构件库的实施者和管理者提供指导，有效地发挥构件库的作用，本文提出了一种可扩展的构件库数据模型ECLDM。该模型以UDDI和BIDM为基础，对其结构进行了修改和扩充，并定义了扩展机制。利用本模型可以有效地描述和管理构件库中各种信息，并可以和UDDI、BIDM进行互操作。     

基于语义检索的构件库系统体系结构

语义检索是解决目前构件查准率和查全率不高的最好方法之一。该文研究了基于语义检索的构件库技术，能在构件入库时完成基于本体的构件语义描述，在检索时复用领域本体，实现构件隐含语义推理和匹配，检索出传统算法难以检索到的构件，为设计实现具体面向语义检索的构件库系统提供了一个参考模型。     

一种改进的案例推理分类方法研究

特征属性的权重分配和案例检索策略对案例推理（Case-based reasoning,CBR）分类的准确率有显著影响. 本文提出一种结合遗传算法、内省学习和群决策思想改进的CBR分类方法. 首先,利用遗传算法得到多组属性权重,再根据内省学习原理对每组权重进行迭代调整;然后,通过案例群检索策略得到满足大多数原则的群决策分类结果;最后,以典型分类数据集的对比实验证明了本文方法能进一步提高CBR分类的准确率. 这表明内省学习可以保证权重分配的合理性,案例群检索策略能充分利用案例库的潜在信息,对提升CBR的学习能力有显著作用.     

Minimum cost service composition in service overlay networks

In service computing, it is often desirable to find the service composition solution for a given service composition request such that the total cost of the service composition solution is minimized. In this paper, we study the problem of finding the minimum cost service composition (MCSC) for a general service composition request which is represented by a directed acyclic graph (DAG). We first prove that the general case of the MCSC problem is NP-Hard. We then show that optimal solutions can be found in polynomial time for some special structured service composition requests. To this end, we derive a sufficient condition on the service composition request graph and propose corresponding algorithms to find the optimal solutions in polynomial time. Using such algorithms as building blocks, we propose heuristic algorithms to decompose the general service composition request graph into service composition request subgraphs with optimal structures. Simulation results demonstrate the effectiveness of the proposed heuristic algorithms.     

Toward perpetually organized unit-load warehouses

Determining the optimal storage assignment for loads in a unit-load warehouse has been extensively addressed in the facility logistics literature. However, the process of implementing a particular storage assignment given the current assignment of loads has not received much attention. Typically, unit-load warehouses use downtime or overtime to remove loads from their current location and move them to the suggested location. This study presents Rearrange-While-Working (RWW) as a strategy to optimize the process of rearranging a warehouse while serving a list of move requests. This study examines three scenarios: (1) one empty location in the warehouse and the material handling equipment (MHE) is idle; (2) one empty location in the warehouse under the RWW strategy; and (3) when there are multiple empty locations in the warehouse under RWW. In the first scenario, the MHE can make any movement desired as it is idle. For the other two scenarios it is assumed that the MHE is not idle so loads can only be moved when requested to perform a move request. Due to the complexity of the problems, several heuristics are proposed. Experimental results indicate that the proposed heuristics perform satisfactorily in terms of solution quality and computational time.     

Toward perpetually organized unit-load warehouses

Determining the optimal storage assignment for loads in a unit-load warehouse has been extensively addressed in the facility logistics literature. However, the process of implementing a particular storage assignment given the current assignment of loads has not received much attention. Typically, unit-load warehouses use downtime or overtime to remove loads from their current location and move them to the suggested location. This study presents Rearrange-While-Working (RWW) as a strategy to optimize the process of rearranging a warehouse while serving a list of move requests. This study examines three scenarios: (1) one empty location in the warehouse and the material handling equipment (MHE) is idle; (2) one empty location in the warehouse under the RWW strategy; and (3) when there are multiple empty locations in the warehouse under RWW. In the first scenario, the MHE can make any movement desired as it is idle. For the other two scenarios it is assumed that the MHE is not idle so loads can only be moved when requested to perform a move request. Due to the complexity of the problems, several heuristics are proposed. Experimental results indicate that the proposed heuristics perform satisfactorily in terms of solution quality and computational time.     

基于PCA和案例推理的煤与瓦斯突出动态预测

为了实现对煤与瓦斯突出快速、准确和动态预测,提出了一种基于主成分分析(PCA)和案例推理(CBR)的煤与瓦斯突出预测方法。考虑煤与瓦斯突出多种影响因素,利用案例推理技术对煤与瓦斯突出危险性进行预测。同时采用一种基于PCA的案例描述特征权值确定方法,以提高案例检索效率以及煤与瓦斯突出预测准确率。利用实测数据对所提方法进行验证,实例验证结果表明,所提方法预测结果的准确性和稳定性更高,预测平均误差和最大误差分别仅为0.154%和0.77%,远小于模糊神经网络方法和专家给定权值的案例推理方法。     

An On-line Multi-CBR Agent Dispatching Algorithm

Case-based reasoning (CBR) is an effective and fast problem-solving methodology, which solves new problems by remembering and adaptation of past cases. With the increasing requests for useful references for all kinds of problems and from different locations, keeping a single CBR system seems to be outdated and not practical. Multi-CBR agents located in different places are of great support to fast meet these requests. In this paper, the architecture of a multi-CBR agent system is proposed, where the CBR agents locate at different places, and are assumed to have the same ability to deal with new problem independently. When the requests in a request queue from different places are coming one by one, we propose a new policy of dispatching which agent to satisfy the request queue. Throughout the paper, we assume that the system must solve the coming request by considering only past requests. In this context, the performance of traditional greedy algorithms is not satisfactory. We apply a new but simple approach – competitive algorithm for on-line problem (called On-line multi-CBR agent dispatching algorithm) to determine the dispatching policy to keep comparative low cost. The corresponding on-line dispatching algorithm is proposed and the competitive ratio is given. Based on the competitive algorithm, the dispatching of multi-CBR agents is optimized.     

An On-Line Multi-CBR Agent Dispatching Algorithm

Case-based reasoning (CBR) is an effective and fast problem-solving methodology, which solves new problems by remembering and adaptation of past cases. With the increasing requests for useful references for all kinds of problems and from different locations, keeping a single CBR system seems to be outdated and not practical. Multi-CBR agents located in different places are of great support to fast meet these requests. In this paper, the architecture of a multi-CBR agent system is proposed, where each CBR agent locates at different places, and is assumed to have the same ability to deal with new problem independently. When requests in a request queue are coming one by one from different places, we propose a new policy of agent dispatching to satisfy the request queue. Throughout the paper, we assume that the system must solve the coming request by considering only past requests. In this context, the performance of traditional greedy algorithms is not satisfactory. We apply a new but simple approach – competitive algorithm for on-line problem (called ODAL) to determine the dispatching policy to keep comparative low cost. The corresponding on-line dispatching algorithm is proposed and the competitive ratio is given. Based on the competitive algorithm, the dispatching of multi-CBR agents is optimized.     

基于期限的多请求数据检索问题研究

给定一个包含多条信道的集合以及一个包含多个请求的集合,其中每一个请求包含多个请求数据项并且希望在一定期限内下载到,基于期限的多请求数据检索问题指当客户配有多条天线时寻找一个在期限内下载多个请求的数据检索序列,使得所有天线的最大访问延迟最小化。大多数现有数据检索方法关注于单个请求或者单条天线,很少研究当客户配有多条天线时多请求的数据检索问题,尤其是每一个请求的检索有时间约束。基于此,本文提出一种多请求的数据检索算法,以调度合适地天线检索这些请求并找到关于这些请求的检索序列,从而平衡在各天线上的访问延迟。针对单请求的数据检索,本文采用最大团思想寻找下载该请求中所有请求数据项的访问模式,使得检索该请求的访问延迟以及期限丢失率最小化。     

钢混构件诊断专家系统的研究与实现

基于不确定推理理论,该文对有关知识进行表达与组织,提出了一种新的采用层次结构的钢混构件诊断知识模型,并给出了专家系统的推理控制策略、冲突解决策略及其算法,最后介绍了专家系统的结构及其组成部分。