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2008 4th International IEEE Conference Intelligent Systems最新文献

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Multi-valued logical method for knowledge extraction and updating in real time 基于多值逻辑的知识提取与实时更新方法
Pub Date : 2008-11-11 DOI: 10.1109/IS.2008.4670545
E. Gegov, B. Vatchova, E. Gegov
Familiar methods for knowledge derivation are based on statistical procedures, which are not accompanied by algorithms for updating of knowledge in real time. In this work, the algorithms are implemented successfully using both logical and statistical procedures whereby flexible arrays of experimental data is entered such that older data is removed and newer data is added. These data are packed together in groups and transformed into logical values of functions of multi-valued logic. The functions are accompanied by probability of occurrence of its values, which is evaluated in real time. In this way, a new construction is formed called multi-valued logical probability function (MLPF), which expresses simultaneously two mutually related correspondences-logical and probabilistic. The correspondences are updated in real time. MLPF is a system of production rules, which are updated in real time.
常见的知识派生方法是基于统计过程的,没有实时更新知识的算法。在这项工作中,算法使用逻辑和统计程序成功实现,其中输入灵活的实验数据阵列,以便删除旧数据并添加新数据。将这些数据分组打包,转化为多值逻辑函数的逻辑值。该函数伴随着其值出现的概率,该概率是实时计算的。这样,就形成了一种新的结构,称为多值逻辑概率函数(MLPF),它同时表达了逻辑和概率两种相互关联的对应关系。通信是实时更新的。MLPF是一个实时更新的生产规则系统。
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引用次数: 3
A fast approach to novelty detection in video streams using recursive density estimation 基于递归密度估计的视频流新颖性快速检测方法
Pub Date : 2008-11-11 DOI: 10.1109/IS.2008.4670523
R. Ramezani, P. Angelov, Xiaowei Zhou
Video-based surveillance and security become extremely important in the new, 21st century for human safety, counter-terrorism, traffic control etc. Visual novelty detection and tracking are key elements of such activities. The current state-of-the-art approaches often suffer from high computational, memory storage costs and from not being fully automated (they usually require a human operator in the loop). This paper introduces a new approach to the problem of novelty detection in video streams that is based on recursive, and therefore, computationally efficient density estimation by a Cauchy type of kernel (as opposed to the usually used Gaussian one). The idea of the proposed approach stems from the recently introduced evolving clustering approach, eClustering and is suitable for online and real-time applications in fully autonomous and unsupervised systems as a stand-alone novelty detector or for priming a tracking algorithm. The approach proposed in this paper has evolving property - it can gradually update the background model and the criteria to detect novelty by unsupervised online learning. The proposed approach is faster by an order of magnitude than the well known kernel density estimation (KDE) method for background subtraction, while having has adaptive characteristics, and does not need any threshold to be pre-specified. Recursive expressions similar to the proposed approach in this paper can also be applied to image segmentation and landmark recognition used for self-localization in robotics. If combined with a real-time prediction using Kalman filter or evolving Takagi-Sugeno fuzzy models a fast and fully autonomous tracking system can be realized with potential applications in surveillance and robotic systems.
在新的21世纪,基于视频的监控和安防在人类安全、反恐、交通管制等方面变得极其重要。视觉新颖性检测和跟踪是此类活动的关键要素。目前最先进的方法通常存在计算和内存存储成本高以及不完全自动化的问题(它们通常需要人工操作)。本文介绍了一种基于递归的视频流新颖性检测问题的新方法,因此,通过柯西核类型(与通常使用的高斯核类型相反)进行计算效率高的密度估计。所提出的方法的思想源于最近引入的不断发展的聚类方法,ecclustering,适用于完全自主和无监督系统中的在线和实时应用,作为独立的新颖性检测器或启动跟踪算法。本文提出的方法具有进化特性,它可以通过无监督在线学习逐步更新背景模型和新颖性检测标准。该方法比已知的核密度估计(KDE)方法的背景减除速度快一个数量级,同时具有自适应特性,并且不需要预先指定任何阈值。与本文提出的方法类似的递归表达式也可以应用于机器人中用于自定位的图像分割和地标识别。如果结合使用卡尔曼滤波或进化Takagi-Sugeno模糊模型的实时预测,可以实现快速和完全自主的跟踪系统,在监视和机器人系统中具有潜在的应用。
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引用次数: 38
Learning in networks: Complex-valued neurons, pruning, and rule extraction 网络中的学习:复值神经元、剪枝和规则提取
Pub Date : 2008-11-11 DOI: 10.1109/IS.2008.4670394
J. Zurada, I. Aizenberg, M. Mazurowski
This paper focuses on neural networks with complex-valued (CV) neurons as well as on selected aspects of neural networks learning, pruning and rule extraction. CV neurons can be used as versatile substitutes in real-valued perceptron networks. Learning of CV layers is discussed in context of traditional multilayer feedforward architecture. Such learning is derivative-free and it usually requires networks of reduced size. Selected examples and applications of CV-networks in bioinformatics and pattern recognition are discussed. The paper also covers specialized learning techniques for logic rule extraction. Such techniques include learning with pruning, and can be used in expert systems, and other applications that rely on models developed to fit measured data.
本文主要研究具有复值(CV)神经元的神经网络,以及神经网络的学习、修剪和规则提取等方面。CV神经元可以作为实值感知器网络的通用替代品。在传统的多层前馈结构背景下讨论了CV层的学习。这种学习是无导数的,通常需要缩小网络的规模。本文讨论了cv网络在生物信息学和模式识别中的应用。本文还涵盖了逻辑规则提取的专门学习技术。这些技术包括通过修剪进行学习,可以用于专家系统和其他依赖于为拟合测量数据而开发的模型的应用程序。
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引用次数: 3
A case-based planning approach to design and plan ITMAS 一个基于案例的规划方法来设计和规划ITMAS
Pub Date : 2008-11-11 DOI: 10.1109/IS.2008.4670479
S. Saberi, Esfandiar Mohammad
Case-based planning which is an induction-based mechanism, has many practical applications in designing and planning of multi-agent systems, which has been recently known as a powerful processing tool in transactional and interactive environments. Intelligent tutoring systems, that have drawn the most attention in the computational mechanisms of concept transition in recent years, have successfully put into practice the concept of multi-agent interaction as well. This paper describes the advances applied in our intelligent tutoring multi-agent system architecture which facilitate meeting the requirements of intelligent tutoring systems and their users. In addition throughout this paper it is explained how case-based planning is utilized for designing and planning the proposed intelligent tutoring multi-agent system to attain an optimized final plan for current user or environment.
基于案例的规划是一种基于归纳的机制,在多智能体系统的设计和规划中有许多实际应用,近年来被认为是事务和交互环境中强大的处理工具。近年来在概念转换计算机制方面备受关注的智能辅导系统也成功地将多智能体交互的概念付诸实践。本文介绍了智能辅导多智能体系统体系结构的研究进展,该体系结构有助于满足智能辅导系统及其用户的需求。此外,本文还解释了如何利用基于案例的规划来设计和规划所提出的智能辅导多智能体系统,以获得针对当前用户或环境的优化最终方案。
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引用次数: 0
Genetic Algorithm approach for Optimal Power Flow with FACTS devices 具有FACTS器件的最优潮流遗传算法
Pub Date : 2008-11-11 DOI: 10.1109/IS.2008.4670477
R. Banu, D. Devaraj
This paper presents a genetic algorithm (GA) based approach for solving the optimal power flow with FACTS devices to eliminate line over loads in the system following single line outages. The proposed approach introduces an index called the single contingency sensitivity (SCS) index to rank the system branches according to their suitability for installing thyristor controlled series capacitors(TCSCs). Once the locations are determined, the problem of identifying the optimal TCSC parameters is formulated as an optimization problem and a GA based approach is applied to solve the optimal power flow (OPF) problem. IEEE 30 bus system is considered to demonstrate the suitability of this algorithm. Case studies on IEEE test system show the effectiveness of this algorithm.
本文提出了一种基于遗传算法的方法,利用FACTS装置求解系统中最优潮流,以消除单线停电后的线路过载。该方法引入了一种称为单应急灵敏度(SCS)指数的指标,根据系统分支是否适合安装晶闸管控制串联电容器(TCSCs)来对系统分支进行排序。一旦位置确定,将TCSC最优参数的辨识问题转化为优化问题,并应用基于遗传算法的方法求解最优潮流问题。以IEEE 30总线系统为例,验证了该算法的适用性。通过对IEEE测试系统的实例分析,验证了该算法的有效性。
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引用次数: 22
Neural network application in strange attractor investigation to detect a FGD 神经网络在奇异吸引子检测中的应用
Pub Date : 2008-11-11 DOI: 10.1109/IS.2008.4670470
Y. Z. Mehran, A. Nasrabadi
There is growing interest in modeling and processing nonlinear behavior in the biological systems. In this paper we applied such methods for detecting Functional Disorder in Gastric. Conventional tools for analyzing such data use information from the power spectral density of the time series, and hence are restricted to little information of data. This information does not provide a sufficient representation of a signal with strong nonlinear properties. In this work, we attempt to extract various nonlinear dynamical invariants of the underlying attractor from the signals. We show that these invariants can discriminate between normal and Functional Gastrointestinal Disorders (FGD) classes.
人们对生物系统非线性行为的建模和处理越来越感兴趣。本文将这些方法应用于胃功能障碍的检测。分析此类数据的传统工具使用来自时间序列的功率谱密度信息,因此受到数据信息很少的限制。该信息不能充分表示具有强非线性特性的信号。在这项工作中,我们试图从信号中提取潜在吸引子的各种非线性动态不变量。我们表明这些不变量可以区分正常和功能性胃肠疾病(FGD)类别。
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引用次数: 1
Neural network - based estimation of reaction rates with partly unknown states and completely known kinetics coefficients 基于神经网络的部分未知状态和完全已知动力学系数的反应速率估计
Pub Date : 2008-11-11 DOI: 10.1109/IS.2008.4670443
P. Georgieva, S. de Azevedo
This work is focused on developing a more efficient computational scheme for estimation of process reaction rates based on NN models. In contrast to the traditional way of process reaction rates estimation by exhaustive and expensive search for the most appropriate parameterized structure, a neural network (NN) based procedure is proposed here to identify the reaction rates in the framework of an analytical process model. The reaction rates are not measured, therefore a special hybrid NN training structure and adaptation algorithm are proposed to make possible the supervised NN learning. The present contribution is focused on the general modelling of a class of nonlinear systems representing several industrial processes including crystallization and precipitation, polymerization reactors, distillation columns, biochemical fermentation and biological systems. The proposed algorithm is further applied for estimation of the sugar crystallization growth rate and compared with alternative solution.
这项工作的重点是开发一种更有效的计算方案,用于估计基于神经网络模型的过程反应速率。传统的过程反应速率估计方法是通过穷举和昂贵的搜索最合适的参数化结构来实现的,与此相反,本文提出了一种基于神经网络(NN)的方法来识别分析过程模型框架中的反应速率。由于不测量反应速率,因此提出了一种特殊的混合神经网络训练结构和自适应算法,使监督式神经网络学习成为可能。目前的贡献是集中在一类非线性系统的一般建模代表几个工业过程,包括结晶和沉淀,聚合反应器,蒸馏塔,生化发酵和生物系统。将该算法进一步应用于糖结晶生长速率的估计,并与备选方案进行了比较。
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引用次数: 0
Optimizing occlusion appearances in 3D association rules visualization 三维关联规则可视化中遮挡现象的优化
Pub Date : 2008-11-11 DOI: 10.1109/IS.2008.4670537
Olivier Couturier, Vincent Dubois, Tien-Ning Hsu, E. Nguifo
Providing efficient and easy-to-use graphical tools to users is a promising challenge for data mining (DM). Visual data mining (VDM) is a new and active research area which goal is to provide powerful and suitable tools for data miners. Some graphical tools have been developed to extract and visualize association rules (AR), among which a three dimension representation where the x-axis is the AR premise, the y-axis is the AR conclusion and the z-axis is a metric value of AR. The 3D approach is one standard representation that is often implemented in many DM tools. However this approach suffers from an overlapping between several objects in the 3D space making some objects unseen or partially truncated. This problem is known as the occlusion problem. In this paper, we propose to formalize it as an optimisation problem of occlusions. Then we define conditions to limit occlusions and finally we propose different heuristics based on ordering of axis-elements, to considerably reduce the number of generated occlusions.
为用户提供高效且易于使用的图形工具是数据挖掘(DM)面临的一个很有前途的挑战。可视化数据挖掘(Visual data mining, VDM)是一个新兴的、活跃的研究领域,其目标是为数据挖掘者提供强大的、合适的工具。已经开发了一些图形工具来提取和可视化关联规则(AR),其中x轴是AR前提,y轴是AR结论,z轴是AR度量值的三维表示。3D方法是许多DM工具中经常实现的一种标准表示。然而,这种方法受到3D空间中多个对象之间重叠的影响,使得一些对象看不见或部分截断。这个问题被称为遮挡问题。在本文中,我们建议将其形式化为遮挡的优化问题。然后我们定义了限制遮挡的条件,最后我们提出了基于轴元素排序的不同启发式方法,以大大减少生成的遮挡数量。
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引用次数: 7
Intelligent component based batch control using IEC61499 and ANSI/ISA S88 基于智能组件的批量控制使用IEC61499和ANSI/ISA S88
Pub Date : 2008-11-11 DOI: 10.1109/IS.2008.4670424
D. Ivanova, Georg Frey, I. Batchkova
This paper proposes an intelligent component based approach for batch control based on ANSI/ISA S88 standard. Common intelligent software components have been built and reused for different application. The components are managed in a control recipe that describes their execution schedule. Furthermore, IEC 61499 standard is adopted as an application framework in which the functional components are implemented as IEC 61499 based function blocks (FB). The operation schedule of the controlled components is then implemented according IEC 61499, based on scheduler-selector-synchronizer (S3) architecture and SIPN models describing the sequence of control execution. An example of the proposed approach based on the real plant for distillation of sulphate turpentine located in Velingrad, Bulgaria is presented and discussed.
提出了一种基于ANSI/ISA S88标准的智能组件批量控制方法。构建了通用的智能软件组件,并为不同的应用重用。组件在描述其执行计划的控制配方中进行管理。此外,采用IEC 61499标准作为应用程序框架,其中功能组件作为基于IEC 61499的功能块(FB)实现。然后,根据IEC 61499,基于调度器-选择器-同步器(S3)体系结构和描述控制执行顺序的SIPN模型,实现受控组件的操作调度。以位于保加利亚维林格勒的硫酸盐松节油蒸馏装置为例,介绍并讨论了该方法的实例。
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引用次数: 9
Optimal decompositions of matrices with grades 带等级矩阵的最优分解
Pub Date : 2008-11-11 DOI: 10.1109/IS.2008.4670530
R. Belohlávek
We present theoretical results regarding decomposition of matrices with grades, i.e. matrices I with entries from a bounded ordered set L such as the real unit interval [0, 1]. If I is such an n times m matrix, we look for a decomposition of I into a product A omicron B of an ntimesk matrix A and a ktimesm matrix B with entries from L with k as small as possible. This problem generalizes the decomposition problem of Boolean factor analysis which is a particular case when L has just two elements 0 and 1. The product we consider is a supt-norm product of which the well known max-min product of Boolean matrices as well as max-min and max-min product of matrices with entries from [0, 1] are particular examples. I, A, and B can be interpreted as object times attribute, object times factor, and factor times attribute matrices describing degrees of expression of attributes on objects, factors on objects, and attributes on factors. In this interpretation, a decomposition I into A omicron B corresponds to discovery of k factors explaining the original data I. We propose to use formal concepts of I in the sense of formal concept analysis as factors. The formal concepts are fixed points of a particular closure operator and can be seen as particular submatrices of I. We prove several results regarding such a decomposition including a theorem which says that decompositions using formal concepts as factors are optimal in that they provide us with the least number of factors possible. Based on the geometrical insight provided by the theorem, we propose a greedy approximation algorithm for finding optimal decompositions. We provide examples illustrating the concepts and implications of the results.
我们给出了关于有等级矩阵分解的理论结果,即矩阵I的条目来自有界有序集合L,如实单位区间[0,1]。如果I是这样一个n乘以m的矩阵,我们寻找I的分解成一个n乘以k的矩阵a和k乘以m的矩阵B的乘积,从L开始,k越小越好。该问题推广了布尔因子分析的分解问题,即当L只有两个元素0和1时的分解问题。我们考虑的积是一种supt-范数积,其中众所周知的布尔矩阵的极大极小积以及元素为[0,1]的矩阵的极大极小积和极大极小积都是特殊的例子。I、A、B可以解释为对象乘以属性、对象乘以因子、因子乘以属性矩阵,分别描述了属性对对象、因素对对象、属性对因素的表达程度。在这种解释中,将I分解为a分元B对应于发现k个解释原始数据I的因素。我们建议在形式概念分析的意义上使用I的形式概念作为因素。形式概念是特定闭包算子的不动点,可以看作是i的特定子矩阵。我们证明了关于这种分解的几个结果,包括一个定理,该定理表明使用形式概念作为因子的分解是最优的,因为它们为我们提供了尽可能少的因子。基于该定理提供的几何洞察力,我们提出了一种寻找最优分解的贪婪逼近算法。我们提供了一些例子来说明这些结果的概念和含义。
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引用次数: 12
期刊
2008 4th International IEEE Conference Intelligent Systems
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