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2009 First Asian Conference on Intelligent Information and Database Systems最新文献

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Stability Analysis of Time-Delay Fuzzy Systems Using Fuzzy Lyapunov Method 用模糊李雅普诺夫方法分析时滞模糊系统的稳定性
Pub Date : 2009-04-01 DOI: 10.1109/ACIIDS.2009.85
K. Yeh, Cheng-Wu Chen, Shu-Hao Lin, Chen-Yuan Chen
This study presents an H-infinite controller design for time-delay Takagi-Sugeno (T-S) fuzzy systems based on the fuzzy Lyapunov method, which is defined in terms of fuzzy blending quadratic Lyapunov functions. The delay-dependent robust stability criterion is derived in terms of the fuzzy Lyapunov method to guarantee the stability of time-delay T-S fuzzy systems subjected to disturbances. Based on the delay-dependent condition and parallel distributed compensation (PDC) scheme, the controller design problem is transformed into solving linear matrix inequalities (LMI).
本文提出了一种基于模糊Lyapunov方法的时滞Takagi-Sugeno (T-S)模糊系统的h -∞控制器设计,该方法由模糊混合二次Lyapunov函数定义。为了保证时滞T-S模糊系统在扰动作用下的稳定性,利用模糊Lyapunov方法导出了时滞相关的鲁棒稳定性判据。基于时滞相关条件和并行分布补偿(PDC)方案,将控制器设计问题转化为求解线性矩阵不等式(LMI)。
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引用次数: 1
Security Policy Integration Method for Information Systems 信息系统安全策略集成方法
Pub Date : 2009-04-01 DOI: 10.1109/ACIIDS.2009.14
T. Tran, N. Nguyen
Policy-based security is an effective and convenient approach to manage information systems. By this approach, we can handle easily all behaviors of a system thought a set of rules. However, conflicts between rules are one of the most common problems we have to deal with in administrative process. In this paper, we propose a new axiomatic approach to solve this problem. Several postulates are presented and analyzed as well as some algorithms are proposed next. The algorithms also have been implemented and tested, and experimental results are presented.
基于策略的安全是一种有效、便捷的信息系统管理方法。通过这种方法,我们可以通过一组规则轻松地处理系统的所有行为。然而,规则之间的冲突是我们在行政管理过程中遇到的最常见的问题之一。在本文中,我们提出了一个新的公理化方法来解决这个问题。提出并分析了几个基本假设,并提出了一些算法。本文对算法进行了实现和测试,并给出了实验结果。
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引用次数: 3
An Agent-Based Workflow System for Assisting in IC Design 基于agent的集成电路设计辅助工作流系统
Pub Date : 2009-04-01 DOI: 10.1109/ACIIDS.2009.12
Guo-Ming Fang, Jim-Min Lin, Zeng-Wei Hong, De-Sheng Chen
A workflow management system is used to provide the automation and reengineering of a process. In an IC design cycle, several software tools are used to support different activities. These tools may be distributed on separate computers. An agent-based workflow management system is proposed in this paper to integrate these tools by using a scripting language. Relevant distributed software tools in agencies are managed by local agents to provide needed services. Mobile agents are used to access these services by following the proposed scripts.
工作流管理系统用于提供流程的自动化和再工程。在一个集成电路设计周期中,几个软件工具被用来支持不同的活动。这些工具可能分布在不同的计算机上。本文提出了一个基于代理的工作流管理系统,通过脚本语言将这些工具集成在一起。代理机构的相关分布式软件工具由本地代理管理,提供所需的服务。通过遵循建议的脚本,使用移动代理来访问这些服务。
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引用次数: 1
A Novel Approach to Keyword Extraction for Contextual Advertising 一种新的上下文广告关键字提取方法
Pub Date : 2009-04-01 DOI: 10.1109/ACIIDS.2009.27
Feng Zhang, Guang Qiu, Jiajun Bu, Mingcheng Qu, Chun Chen
Online advertising has now turned to be one of the major revenue sources for today's Internet companies. Among the different channels of advertising, contextual advertising takes the great part. There are already lots of studies done for the keyword extraction problem in contextual advertising for English, however, little has been conducted for Chinese, which is mainly different from English linguistically. In this paper, we focus on the problem of Chinese advertising keywords extraction and propose a novel approach based on the idea of classification. We adopt C4.5 as the classifier model and select appropriate features with Chinese linguistic characteristic taken into consideration. The experimental results indicate that our approach is promising.
在线广告现在已经成为当今互联网公司的主要收入来源之一。在不同的广告渠道中,语境广告占了很大的比重。针对英语语境广告中的关键词提取问题已有大量的研究,但针对汉语语境广告的关键词提取问题的研究却很少,汉语语境广告的关键词提取与英语语境广告的关键词提取有着很大的语言差异。本文针对中文广告关键词抽取问题,提出了一种基于分类思想的中文广告关键词抽取方法。我们采用C4.5作为分类器模型,并结合汉语的语言特点选择合适的特征。实验结果表明,我们的方法是有希望的。
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引用次数: 7
Argument Based Machine Learning from Examples and Text 基于实例和文本的论证机器学习
Pub Date : 2009-04-01 DOI: 10.1109/ACIIDS.2009.60
M. Mozina, C. Giuliano, I. Bratko
We introduce a novel approach to cross-media learning based on argument based machine learning (ABML). ABML is a recent method that combines argumentation and machine learning from examples, and its main idea is to use arguments for some of the learning examples. Arguments are usually provided by a domain expert. In this paper, we present an alternative approach, where arguments used in ABML are automatically extracted from text with a technique for relation extraction. We demonstrate and evaluate the approach through a case study of learning to classify animals by using arguments automatically extracted from Wikipedia.
我们介绍了一种基于基于参数的机器学习(ABML)的跨媒体学习方法。ABML是一种结合论证和机器学习实例的新方法,其主要思想是对一些学习实例使用论证。参数通常由领域专家提供。在本文中,我们提出了一种替代方法,其中ABML中使用的参数通过关系提取技术自动从文本中提取。我们通过使用从维基百科中自动提取的参数来学习对动物进行分类的案例研究来演示和评估这种方法。
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引用次数: 3
A Structural Sampling Technique for Better Decision Trees 一种更好的决策树结构抽样技术
Pub Date : 2009-04-01 DOI: 10.1109/ACIIDS.2009.24
H. Sug
Since data mining problems contain a large amount of data, sampling is a necessity for the success of the task. Decision trees have been developed for prediction, and finding decision trees with smaller error rates has been a major task for their success. This paper suggests a structural sampling technique that is based on a generated decision tree, where the tree is generated based on fast and dirty tree generation algorithm. Experiments with several sample sizes and representative decision tree algorithms showed that the method is more effective with respect to decision tree size and error rate than conventional random sampling method especially for small sample size.
由于数据挖掘问题包含大量数据,因此采样是任务成功的必要条件。决策树是为预测而开发的,寻找错误率较小的决策树是其成功的主要任务。本文提出了一种基于生成决策树的结构采样技术,其中决策树是基于快速脏树生成算法生成的。不同样本量和代表性决策树算法的实验表明,该方法在决策树大小和错误率方面都优于传统的随机抽样方法,特别是在小样本量情况下。
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引用次数: 2
Application to GA-Based Fuzzy Control for Nonlinear Systems with Uncertainty 基于遗传算法的非线性不确定系统模糊控制中的应用
Pub Date : 2009-04-01 DOI: 10.1109/ACIIDS.2009.86
Po-Chen Chen, K. Yeh, Cheng-Wu Chen, Chen-Yuan Chen
In this study, we strive to combine the advantages of fuzzy theory, genetic algorithms (GA), H-infinite tracking control schemes, smooth control and adaptive laws to design an adaptive fuzzy sliding model controller for the rapid and efficient stabilization of complex and nonlinear systems. First, we utilize a reference model and a fuzzy model (both involvingrules) to describe and well-approximate an uncertain, nonlinear plant. The FLC rules and the consequent parameter are decided on via GA. A boundary-layer function is introduced into these updated laws to cover modeling errors and to guarantee that the state errors converge into a specified error bound. After this, a H-infinite tracking problem is characterized. We solve an eigenvalue problem (EVP), and derive a modified adaptive neural network controller (MANNC) to simultaneously stabilize and control the system and achieve H-infinite control performance.
在本研究中,我们努力结合模糊理论、遗传算法(GA)、h -∞跟踪控制方案、平滑控制和自适应律的优点,设计一种自适应模糊滑模控制器,用于复杂非线性系统的快速有效镇定。首先,我们利用一个参考模型和一个模糊模型(都包含规则)来描述和很好地逼近一个不确定的非线性对象。通过遗传算法确定FLC规则和相应参数。在这些更新的定律中引入边界层函数来掩盖建模误差,并保证状态误差收敛到指定的误差界内。在此基础上,对h∞跟踪问题进行了表征。在求解特征值问题(EVP)的基础上,推导出一种改进的自适应神经网络控制器(MANNC),实现了系统的同时稳定和控制,实现了h -∞的控制性能。
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引用次数: 62
Rotational Invariant Wood Species Recognition through Wood Species Verification 基于树种验证的旋转不变树种识别
Pub Date : 2009-04-01 DOI: 10.1109/ACIIDS.2009.10
J. Y. Tou, Yong Haur Tay, P. Lau
An automated wood species recognition system using computer vision techniques is not widely used today, it is highly needed in various industries, but a wood identification expert is not easily trained to meet the market demand. This paper proposes a rotational invariant method using the grey level co-occurrence matrices (GLCM) as the features, an energy value representing the similarity between the test sample and the template is computed to decide whether the test sample is the same species as the template. A template is accepted when the energy is lower than the threshold value. The species with the highest number of accepted templates will be regarded as the recognition result. The experiment is conducted on six wood species of the CAIRO dataset with a total of 450 training samples and 60 testing samples and achieved a result of 80.00%.
采用计算机视觉技术的自动化树种识别系统在当今应用并不广泛,在各个行业中都有很高的需求,但是木材识别专家的培养很难满足市场的需求。本文提出了一种以灰度共生矩阵(GLCM)为特征的旋转不变方法,通过计算一个表示测试样本与模板相似度的能量值来判断测试样本是否与模板属于同一物种。当能量低于阈值时,接受模板。被接受模板数量最多的物种将被视为识别结果。在CAIRO数据集的6种木材上进行了实验,总共有450个训练样本和60个测试样本,实验结果达到了80.00%。
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引用次数: 32
A New Model to Short-Term Power Load Forecasting Combining Chaotic Time Series and SVM 混沌时间序列与支持向量机相结合的短期电力负荷预测新模型
Pub Date : 2009-04-01 DOI: 10.1109/ACIIDS.2009.22
D. Niu, Yongli Wang
Accurate forecasting of electricity load has been one of the most important issues in the electricity industry. Recently, along with power system privatization and deregulation, accurate forecast of electricity load has received increasing attention. According to the chaotic and non-linear characters of power load data, the model of support vector machines (SVM) based on Lyapunov exponents was established. The time series matrix was established according to the theory of phase-space reconstruction, and then Lyapunov exponents was computed to determine time delay and embedding dimension. Then support vector machines algorithm was used to predict power load. In order to prove the rationality of chosen dimension, another two random dimensions were selected to compare with the calculated dimension. And to prove the effectiveness of the model, BP algorithm was used to compare with the result of SVM. The results show that the model is effective and highly accurate in the forecasting of short-term power load. It is denoted that the model combining SVM and chaotic time series learning system has advantage than other models.
电力负荷的准确预测一直是电力行业最重要的问题之一。近年来,随着电力系统的民营化和放松管制,电力负荷的准确预测越来越受到人们的重视。根据电力负荷数据的混沌和非线性特点,建立了基于李雅普诺夫指数的支持向量机模型。根据相空间重构理论建立时间序列矩阵,通过计算Lyapunov指数确定时延和嵌入维数。然后采用支持向量机算法对电力负荷进行预测。为了证明所选维数的合理性,随机选取另外两个维数与计算维数进行比较。为了证明该模型的有效性,将BP算法与支持向量机的结果进行了比较。结果表明,该模型在短期电力负荷预测中具有较高的准确性和有效性。结果表明,将支持向量机与混沌时间序列学习系统相结合的模型优于其他模型。
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引用次数: 3
Agent-Based Generation of Personal Thesaurus 基于代理的个人词库生成
Pub Date : 2009-04-01 DOI: 10.1109/ACIIDS.2009.88
Grzegorz Popek, R. Katarzyniak
An agent autonomously develops thesaurus which is an opposite to a typical situation in which agents are delivered with a thesaurus proposed by a designer. The agent uses concepts which emerged from the process of semiosis. These concepts are modeled as values of linguistic variable, and therefore, a single fuzzy variable can be correlated with each of them. Also,they can be paired with linguistic hedges (very,slightly, etc.). An agent finds types of relations between concepts (very, slightly, less general than, ...) based on presented commonsense requirements and a similarity between different concepts and combinations hedge concept.In the end, all relations are gathered together by a proposed algorithm to compose a private self-developed thesaurus.
代理自主开发同义词典,这与典型的情况相反,在这种情况下,代理与设计师提出的同义词典一起交付。代理使用从符号学过程中产生的概念。这些概念被建模为语言变量的值,因此,单个模糊变量可以与每个概念相关联。此外,它们还可以与语言限制语(very,slightly,等等)搭配使用。智能体根据提出的常识性要求和不同概念之间的相似性以及对冲概念的组合,找到概念之间的关系类型(非常、稍微、不那么一般)。最后,通过提出的算法将所有关系聚集在一起,组成一个私有的自开发词库。
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引用次数: 2
期刊
2009 First Asian Conference on Intelligent Information and Database Systems
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