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2009 IEEE International Conference on Granular Computing最新文献

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On SP-closedness in L-topological spaces 论l -拓扑空间中的sp -闭性
Pub Date : 2010-05-11 DOI: 10.1109/ICICTA.2010.759
S. Bai, Li-Wei Jiang
By means of semi-pre-open L-sets and their inequality, a new form of SP-closedness is introduced in L-topological spaces, where L is a complete De Morgan algebra. This new form does not depend on the structure of basis lattice L and L does not require any distributivity.
利用半预开L集及其不等式,在L拓扑空间中引入了一种新的sp -闭性形式,其中L是完全De Morgan代数。这种新形式不依赖于基格L的结构,且L不需要任何分布性。
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引用次数: 0
Using Granular Computing theories for service-oriented systems analysis and design 使用颗粒计算理论进行面向服务的系统分析和设计
Pub Date : 2009-09-22 DOI: 10.1109/GRC.2009.5255118
Wei Huang, E. El-Darzi
Over the past decade, granular computing has rapidly emerged as a new paradigm for distributed information systems. This paper describes an approach to develop service-oriented systems with granular computing theories and OMG standard UML (Unified Modelling Language)[1,4]. The paper goes on to outline how to integrate granular computing structures, methodology and UML for modelling, organising and addressing systems through a case study of emergency assistance service system (EAS). Our approach to building software development solutions emphasizes the importance of using granular computing structures, methodology and domain modelling as a critical initial step in developing and producing software architectures and applications. It aims to present an effective schedule and plan for software development process and addressing activities characteristics, whilst reducing the complexity of the complex systems' design and development by exploiting granular computing and UML's productivity potential.
在过去的十年中,颗粒计算迅速成为分布式信息系统的新范式。本文描述了一种利用粒度计算理论和OMG标准UML(统一建模语言)开发面向服务系统的方法[1,4]。本文通过紧急援助服务系统(EAS)的案例研究,概述了如何将颗粒计算结构、方法和UML集成到建模、组织和寻址系统中。我们构建软件开发解决方案的方法强调使用颗粒计算结构、方法和领域建模作为开发和生产软件架构和应用程序的关键初始步骤的重要性。它旨在为软件开发过程和处理活动特征提供一个有效的时间表和计划,同时通过利用颗粒计算和UML的生产力潜力来减少复杂系统设计和开发的复杂性。
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引用次数: 2
Wavelet neural network based on BP algorithm and its application in flood forecasting 基于BP算法的小波神经网络及其在洪水预报中的应用
Pub Date : 2009-09-22 DOI: 10.1109/GRC.2009.5255121
Ping Hu
As is well known, it is the application of runoff flood forecasting that is extraordinary significant for us. A detailed detection of the flood forecasting process has been carried out using powerful artificial neural network in this paper. Learning algorithmof wavelet neural network was produced by extruding it in BP idea.The determination of network hiddenlayer nodes utilizes the medthod of tring fault. Activation function belongs to morlet wavelet function, and the modle of net structure belongs to 371. It is shown that the reliable prediction accury could be provided by using this model for predicting and analysising for the flood data of solar Da in 1996.
众所周知,径流洪水预报的应用对我们来说意义非凡。本文利用强大的人工神经网络对洪水预报过程进行了详细的检测。利用BP思想对小波神经网络进行挤压,得到小波神经网络的学习算法。网络隐藏层节点的确定采用故障检测的方法。激活函数属于morlet小波函数,网络结构模型属于371。结果表明,利用该模型对1996年太阳日的洪水资料进行预测和分析,可以提供可靠的预测精度。
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引用次数: 4
Multi-objective particle swarm optimization algorithm for engineering constrained optimization problems 工程约束优化问题的多目标粒子群优化算法
Pub Date : 2009-09-22 DOI: 10.1109/GRC.2009.5255064
D. Tan, Wenhai Luo, Qing Liu
This paper proposes a modified particle swarm optimization algorithm for engineering optimization problems with constraints, in which the penalty function is employed to the traditional PSO algorithm, and at the same time adjusts the personal optimum and global optimum to make PSO being able to solve the non-linear programming problems, then the multi-objective problem can be converted into single objective problem. Moreover, the constraint term played its role in the process of generating particles, those pariticles which don't meet the constraint condition are eliminated. The actual engineering design optimization problem is tested and the results show that the multi-objective particle swarm optimization algorithm can be used to solve the multi-objective constrained optimization problem. Comparison with Genetic Algorithm confirms that the proposed algorithm can find better solutions, and converge quickly.
提出了一种改进的粒子群优化算法,该算法将惩罚函数引入到传统粒子群优化算法中,同时对个体最优和全局最优进行调整,使粒子群优化算法能够求解非线性规划问题,从而将多目标问题转化为单目标问题。此外,约束项在粒子生成过程中发挥了作用,剔除了不满足约束条件的粒子。对实际工程设计优化问题进行了测试,结果表明,多目标粒子群优化算法可用于解决多目标约束优化问题。与遗传算法的比较表明,该算法能较好地找到解,收敛速度快。
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引用次数: 9
The research and implementation of a correlative degree mining algorithm based on IIS logs 基于IIS日志的关联度挖掘算法的研究与实现
Pub Date : 2009-09-22 DOI: 10.1109/GRC.2009.5255028
Lei-Yue Yao, Jianying Xiong
In order to find out the user patterns that hide in web logs, log mining technology is one of the best ways. Log mining is the usage of data mining in the field of web server' logs. Although there are a set of softwares which can be used to analysis web logs, the algorithm raised in this article pay special attention to discover the relationship among all the pages of the web site. In this algorithm, size-link radio and static inner-link degree was creative used. According to the result of experiment, this algorithm can exactly find out the correlative ones among massive pages.
为了发现隐藏在web日志中的用户模式,日志挖掘技术是最好的方法之一。日志挖掘是数据挖掘在web服务器日志领域的应用。虽然已经有一套软件可以用来分析网站日志,但本文提出的算法特别注重发现网站各页面之间的关系。该算法创造性地使用了尺寸链接无线电和静态内链接度。实验结果表明,该算法能够准确地找出海量页面之间的相关信息。
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引用次数: 1
Ubiquitous personalized information processing with wildcards 使用通配符处理无处不在的个性化信息
Pub Date : 2009-09-22 DOI: 10.1109/GRC.2009.5255135
Xindong Wu
With the rapid development of computer, communication and networking technologies, Web information resources are becoming increasingly rich, and on-line applications are required to be more and more flexible. Therefore, a new generation of information models and mechanisms for these information processing requirements has become a major challenge. This talk will discuss four scientific problems in ubiquitous personalized information processing with wildcards*, including demand driven aggregation of information resources, mining and analysis for aggregated information, user interest modeling, and system security. With these four components, a pervasive and personalized information processing mechanism can be constructed for dynamically organizing and optimizing multiple information resources, implementing a transparent and scalable information processing architecture, and flexibly building information and analysis services to meet various user demands.
随着计算机、通信和网络技术的飞速发展,Web信息资源日益丰富,对在线应用的要求也越来越灵活。因此,新一代的信息模型和机制已成为这些信息处理需求的主要挑战。本讲座将讨论在泛在的个性化信息处理中使用通配符*的四个科学问题,包括需求驱动的信息资源聚合、聚合信息的挖掘和分析、用户兴趣建模和系统安全。通过这四个组件,可以构建普适、个性化的信息处理机制,动态组织和优化多种信息资源,实现透明、可扩展的信息处理体系结构,灵活构建信息和分析服务,满足不同用户需求。
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引用次数: 0
An approach to XML Path retrieval 一种XML路径检索方法
Pub Date : 2009-09-22 DOI: 10.1109/GRC.2009.5255069
Ling Song, Shengen Li, Wei Cui, Dongmei Zhang, Xiaofei Niu
Both of XML document and user's query are represented by the set of paths from the root node to leaf nodes. So the context and content information contained in the corresponding path is a vital important clue to research XML retrieval. This paper presents an approach, NPathSim, for measuring similarity between two paths. XML Path retrieval was performed to evaluate the performance of NPathSim. The experiments show that our path retrieval method can achieve better performance than other methods.
XML文档和用户查询都由从根节点到叶节点的一组路径表示。因此,相应路径中包含的上下文和内容信息是研究XML检索的重要线索。本文提出了一种测量两条路径之间相似度的方法NPathSim。通过XML路径检索来评估NPathSim的性能。实验表明,本文提出的路径检索方法比其他方法具有更好的检索性能。
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引用次数: 1
Study on question answering system for biomedical domain 生物医学领域问答系统的研究
Pub Date : 2009-09-22 DOI: 10.1109/GRC.2009.5255043
Bo Xu, Hongfei Lin, Baoyan Liu
This paper focuses on setting up a question-answering oriented Biomedical Domain, and it applies several different approaches to the different processing phases. Firstly, it uses shallow parser to identify the types of questions and extract the keywords, and the keywords are expanded with UMLS for the purpose of improving the recall. Secondly, passage retrieval is performed with the expanded keywords. Lastly, in the phase of answering extracting, the approach of passage retrieval based on hotspots is presented to discover the related information with low redundancy. This QA system has been evaluated on the dataset of TREC, and the experiment results shows that it can answer the questions from biomedical domain effectively.
本文的重点是建立一个面向问答的生物医学领域,并在不同的处理阶段应用了几种不同的方法。首先,使用浅解析器识别问题类型并提取关键词,对关键词进行UMLS扩展,以提高查全率。其次,利用扩展后的关键词进行文章检索。最后,在回答提取阶段,提出了基于热点的通道检索方法,以发现低冗余的相关信息。在TREC数据集上对该问答系统进行了测试,实验结果表明该问答系统能够有效地回答来自生物医学领域的问题。
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引用次数: 1
Maritime information engine 海事信息机
Pub Date : 2009-09-22 DOI: 10.1109/GRC.2009.5255013
Xinxin Zhao, Xiaofeng Wang
Set the Chinese text sets into two classifications and determine whether the information is in the field of Chinese maritime by a two-classifier which is guided by multiple semantic. Eventually it gets Chinese maritime information set so that we can custom maritime information. We call this information system for the Chinese Marine engine. Experiments show that the Chinese Marine engine achieves good effects of custom the Chinese maritime information and it has a high practical value.
将中文文本集分为两类,利用多语义引导下的双分类器判断信息是否属于中文海事领域。最终得到中文海事信息集,方便用户自定义海事信息。我们称之为中国船用发动机信息系统。实验结果表明,该中文海事机在中文海事信息提取方面取得了较好的效果,具有较高的实用价值。
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引用次数: 1
Classification using Markov blanket for feature selection 分类使用马尔可夫毯进行特征选择
Pub Date : 2009-09-22 DOI: 10.1109/GRC.2009.5255023
Yi-feng Zeng, Jian Luo, Shuyuan Lin
Selecting relevant features is in demand when a large data set is of interest in a classification task. It produces a tractable number of features that are sufficient and possibly improve the classification performance. This paper studies a statistical method of Markov blanket induction algorithm for filtering features and then applies a classifier using the Markov blanket predictors. The Markov blanket contains a minimal subset of relevant features that yields optimal classification performance. We experimentally demonstrate the improved performance of several classifiers using a Markov blanket induction as a feature selection method. In addition, we point out an important assumption behind the Markov blanket induction algorithm and show its effect on the classification performance.
在分类任务中需要大量数据集时,需要选择相关特征。它产生了足够多的可处理的特征,这些特征可能会提高分类性能。本文研究了马尔可夫包层归纳算法对特征进行过滤的统计方法,然后利用马尔可夫包层预测器应用分类器。马尔可夫包层包含产生最佳分类性能的相关特征的最小子集。我们通过实验证明了使用马尔可夫毯归纳作为特征选择方法的几种分类器的改进性能。此外,我们指出了马尔可夫毯子归纳算法背后的一个重要假设,并展示了它对分类性能的影响。
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引用次数: 16
期刊
2009 IEEE International Conference on Granular Computing
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