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复杂网络聚类方法   总被引:43,自引:2,他引:41       下载免费PDF全文
网络簇结构是复杂网络最普遍和最重要的拓扑属性之一,具有同簇节点相互连接密集、异簇节点相互连接稀疏的特点.揭示网络簇结构的复杂网络聚类方法对分析复杂网络拓扑结构、理解其功能、发现其隐含模式、预测其行为都具有十分重要的理论意义,在社会网、生物网和万维网中具有广泛应用.综述了复杂网络聚类方法的研究背景、研究意义、国内外研究现状以及目前所面临的主要问题,试图为这个新兴的研究方向勾画出一个较为全面和清晰的概貌,为复杂网络分析、数据挖掘、智能Web、生物信息学等相关领域的研究者提供有益的参考.  相似文献
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自主式机器人群体行为的进化计算实现   总被引:4,自引:2,他引:2  
本文探讨机器人在特定任务下如何通过遗传算法选择合适的传感器和行为参数来进化出多个 自主式移动机器人之间的优化群体行为.  相似文献
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基于OWL和Horn子句的β-PSML语言框架   总被引:2,自引:2,他引:0  
提出了将OWL和Horn子句相结合构建β-PSML语言,它既可以表示OWL中不能表示的多元关系,又可以表示Horn子句难以表示的有丰富等级结构的领域模型。提出的β-PSML语言是一种语义Web中新的知识表示方法,利用该β-PSML语言的推理功能可以完成语义Web中的查询。  相似文献
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苏依拉  郑磊  刘椿年  钟宁  LIU Jiming 《计算机工程》2005,31(23):146-147,168
随着Web的发展,用户检索有用的信息变得越来越难。因此,在Web环境下,迫切需要研发相应的系统解决这个问题。而这一系统的核心是问题解决标记语言和基于PSML语言的Web推理引擎。该文提出了β-PSML语言的推理算法,并说明了某些查询仅使用Prolog或OWL其中之一的推理引擎无法得到结果,只有通过结合Prolog和OWL二者的推理引擎进行推理才能得出结果。实验结果表明该方法是有效的,原型系统在语义Web上可得到良好的结果。  相似文献
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该文根据产品数据管理(PDM)技术的特点,在产品信息模型的基础上,分析了维修性信息的构成与分类,采用面向对象技术初步建立了基于PDM环境的产品维修性信息模型,并简要阐述了建立这种信息模型的现实意义。  相似文献
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Complex network theory provides a means for modeling and analyzing complex systems that consist of multiple and interdependent components. Among the studies on complex networks, structural analysis is of fundamental importance as it presents a natural route to understanding the dynamics, as well as to synthesizing or optimizing the functions, of networks. A wide spectrum of structural patterns of networks has been reported in the past decade, such as communities, multipartites, bipartite, hubs, authorities, outliers, and bow ties, among others. In this paper, we are interested in tackling the challenging task of characterizing and extracting multiplex patterns (multiple patterns as mentioned previously coexisting in the same networks in a complicated manner), which so far has not been explicitly and adequately addressed in the literature. Our work shows that such multiplex patterns can be well characterized as well as effectively extracted by means of a granular stochastic blockmodel, together with a set of related algorithms proposed here based on some machine learning and statistical inference ideas. These models and algorithms enable us to further explore complex networks from a novel perspective.  相似文献
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Most real-world distribution systems can be modeled as distribution networks, where a commodity can flow from source nodes to sink nodes through junction nodes. One of the fundamental characteristics of distribution networks is the functional robustness, which reflects the ability of maintaining its function in the face of internal or external disruptions. In view of the fact that most distribution networks do not have any centralized control mechanisms, we consider the problem of how to improve the functional robustness in a decentralized way. To achieve this goal, we study two important problems: 1) how to formally measure the functional robustness, and 2) how to improve the functional robustness of a network based on the local interaction of its nodes. First, we derive a utility function in terms of network entropy to characterize the functional robustness of a distribution network. Second, we propose a decentralized network pricing mechanism, where each node need only communicate with its distribution neighbors by sending a "price" signal to its upstream neighbors and receiving "price" signals from its downstream neighbors. By doing so, each node can determine its outflows by maximizing its own payoff function. Our mathematical analysis shows that the decentralized pricing mechanism can produce results equivalent to those of an ideal centralized maximization with complete information. Finally, to demonstrate the properties of our mechanism, we carry out a case study on the U.S. natural gas distribution network. The results validate the convergence and effectiveness of our mechanism when comparing it with an existing algorithm.  相似文献
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