检索结果-内蒙古大学图书馆

2011 American Control Conference (ACC)

作者： Haixia Su Yingmin Jia Junping Du Fashan Yu Seventh Research Division and the Department of Systems and Control Beihang University Beijing China Key Laboratory of Mathematics Informatics and Behavioral Semantics (LMIB) Ministry of Education SMSS Beihang University Beijing China Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia School of Computer Science and Technology Beijing University of Posts and Telecommunications Beijing China School of Electrical Engineering and Automation Henan Polytechnic University Jiaozuo Henan China

In this paper, an adaptive iterative learning control (ILC) scheme is proposed for trajectory tracking of uncertain delay systems based on model matching technique. The reference model is a delay system operating over in a finite time interval. An iterative model matching controller is designed and an iteration domain adaptive law is chosen to estimate the unknown parameters. It shows that the model matching technique can be applied in a straightforward method to ILC problem. A simulation example is included to illustrate the designed scheme.

关键词： Adaptation models Polynomials Adaptive systems Delay effects Delay systems

来源：评论

学校读者我要写书评

暂无评论

Application of clickstream analysis as Web page importance metric in parallel crawlers

Application of clickstream analysis as Web page importance m...

引用

2010 International Symposium on Information Technology, ITSim'10

作者： Selamat, Ali Ahmadi-Abkenari, Fatemeh Intelligent Software Engineering Laboratory Faculty of Computer Science and Information Systems Universiti Teknologi Malaysia 81310 UTM Skudai Johor Malaysia

ISBN: (纸本)9781424467181

Employing a parallel crawler as a multi processes crawler causes different issues of concern in comparison to applying a single-process crawler. These issues impact on achieving the results with higher or even the same quality from a parallel crawler in comparison to a centralized one. Existed parallel crawlers' architectures employ link dependant metrics -such as Backlink count or PageRank - for URL importance determination in order to prioritize the queue of each process. Then the specific number of the most important pages is sent to the index section of the crawler for further processing on their content. Application of metrics with link dependent nature causes considerable overhead on the overall parallel crawler resulted from the link information exchange among different processes. In this paper we propose the application of clickstream analysis as a link independent Web page importance metric in a parallel crawler. Our approach includes proposing an algorithm for a balanced performance of different processes within a parallel crawler which results in the discovery of higher quality pages by the overall parallel crawler with less overhead in comparison to a centralized crawler which employs link dependant metrics of importance. © 2010 IEEE.

关键词： Web crawler

来源：评论

学校读者我要写书评

暂无评论

Modified relevance feedback for content based image retrieval using support machine

Modified relevance feedback for content based image retrieva...

引用

15th International Symposium on Artificial Life and Robotics, AROB '10

作者： Lim, Pei-Geok Selamat, Ali Intelligent Software Engineering Laboratory Faculty of Computer Science and Information Systems Universiti Teknologi Malaysia 81310 UTM Skudai Johor Malaysia

ISBN: (纸本)9784990288044

The rapid growth of the computer technologies and the advent of World Wide Web have increased the amount and the complexity of multimedia information. Content-based image retrieval (CBIR) system has been developed as an efficient image retrieval tool whereby user can provide their query to the system to allow it to retrieve the user's desired image from image database. However, the traditional relevance feedback of CBIR has some limitations that decrease the performance of the CBIR system that are the imbalance of training set problem, classification problem, limited information from user problem, and insufficient training set problem. Therefore, in this paper we propose a modified relevant feedback method to support the user query and user profiles based on the weight ranking of the image retrieved. The Support Vector Machine (SVM) has been used to support the learning process in order to reduce the semantic gap between user and the CBIR system. From the experiments, the proposed learning method has enabled the users to improve their search results based on the precision and accuracy. © 2010 ISAROB.

关键词： Support vector machines

来源：评论

学校读者我要写书评

暂无评论

Recording how-provenance on probabilistic databases

Recording how-provenance on probabilistic databases

引用

12th International Asia Pacific Web Conference, APWeb 2010

作者： Gao, Ming He, Xiangnan Jin, Cheqing Wang, Xiaoling Zhou, Aoying Shanghai Key Laboratory of Intelligent Information Processing Fudan University Shanghai China Software Engineering Institute East China Normal University Shanghai China

ISBN: (纸本)9780769540122

Tracking data provenance (or lineage) has become increasingly important in many large-scale applications, and a few methods have been proposed to record data provenance recently. However, most of previous works mainly focus on deterministic databases except Trio style lineage that aims at probabilistic databases, which is much more challenging because of the exponential growth of possible world instances and dependence among intermediate tuples. This paper proposes an approach, named PHP-tree, to model how-provenance upon probabilistic databases. we also show how to evaluate probability based on a PHP-tree. Compared with Trio style lineage, our approach is independent of intermediate results and can calculate the probability both cases of restricted and complete propagation of data provenance. Detailed experimental results show the effectiveness, efficiency and scalability of our proposed model. © 2010 IEEE.

关键词： Database systems

来源：评论

学校读者我要写书评

暂无评论

Reports of the AAAI 2010 fall symposia

Reports of the AAAI 2010 fall symposia

引用

作者： Azevedo, Roger Biswas, Gautam Bohus, Dan Carmichael, Ted Finlayson, Mark A. Hadzikadic, Mirsad Havasi, Catherine Horvitz, Eric Kanda, Takayuki Koyejo, Oluwasanmi Lawless, William F. Lenat, Doug Meneguzzi, Felipe Mutlu, Bilge Oh, Jean Pirrone, Roberto Raux, Antoine Sofge, Donald A. Sukthankar, Gita Van Durme, Benjamin Yorke-Smith, Neil Department of Educational and Counseling Psychology McGill University Canada Center for Intelligent Systems Vanderbilt University United States Microsoft Research Redmond United States Department of Software and Information Systems University of North Carolina Charlotte United States Complex Systems Institute United States Computer Science and Artificial Intelligence Laboratory Massachusetts Institute of Technology United States Media Lab. Massachusetts Institute of Technology United States ATR Intelligent Robotics and Communication Laboratories Kyoto Japan Department of Electrical and Computer Engineering University of Texas Austin United States Department of Mathematics Paine College Augusta GA United States Cycorp Austin TX United States Robotics Institute Carnegie Mellon University United States Department of Computer Sciences University of Wisconsin Madison United States University of Palermo Italy Honda Research Institute United States Navy Center for Applied Research in Artificial Intelligence Naval Research Laboratory Washington DC United States Department of Electrical Engineering and Computer Science University of Central Florida United States Department of Computer Science Johns Hopkins University United States American University of Beirut Lebanon SRI International's Artificial Intelligence Center United States

The Association for the Advancement of Artificial Intelligence (AAAI) presented the 2010 Fall Symposium Series on November 11-13, 2010. The eight symposia included Cognitive and Metacognitive Educational Systems, Commonsense Knowledge, Complex Adaptive Systems: Resilience, Robustness, and Evolvability, Computational Models of Narrative, Dialog with Robots, Manifold Learning and Its Applications, Proactive Assistant Agents and Quantum Informatics for Cognitive, Social, and Semantic Processes. Cognitive and Metacognitive Educational Systems aimed to provide a comprehensive definition of metacognitive educational systems that is inclusive of the theoretical, architectural, and educational aspects of this field. The AAAI Commonsense Knowledge Fall Symposium had the goal of bringing together the diverse elements of this community whose work benefits from or contributes to the representation of general knowledge about the world. One of the specific goals of Proactive symposium was to gather the researchers from various projects in assistant agents to share their wisdom in retrospect.

关键词： Semantics

来源：评论

学校读者我要写书评

暂无评论

Efficient SLCA computing service for XML filtering in IaaS

Efficient SLCA computing service for XML filtering in IaaS

引用

12th International Asia Pacific Web Conference, APWeb 2010

作者： Zhang, Chenjing Wang, Xiaoling Zhou, Aoying Shanghai Key Laboratory of Intelligent Information Fudan University China College of Information Technology Shanghai Ocean University China Shanghai Key Laboratory of Trustworthy Computing Software Engineering Institute East China Normal University China

ISBN: (纸本)9780769540122

Cloud provides dynamically computing services for large scales of data over the Internet. IaaS(information as a service) is one of utilities to provide information service in Cloud computing. Large scales of XML data are produced continually in Internet. Efficient information filtering services are needed. Previous XML filter approaches aim at XPath queries. However, many users tend to use keywords to describe requirements. SLCA (Smallest Lowest Common Ancestor)-based XML keyword search is one of the most important information retrieval approaches. Former approaches focus on building centralized index for a large scale of XML document collection and can't process continuous XML streams. This paper addresses SLCA computing service for continuous XML document. A novel SLCA computing service is designed, where SLCAs are obtained in one scan of XML stream. We demonstrate the efficiency of our algorithms analytically and experimentally. © 2010 IEEE.

关键词： XML

来源：评论

学校读者我要写书评

暂无评论

Feedback iterative learning control for time-delay systems based on 2D analysis approach

引用

控制理论与应用（英文版） 2010年第4期8卷 457-463页

作者： Deyuan MENG Yingmin JIA Junping DU Shiying YUAN The Seventh Research Division Beihang University Beijing 100191 China Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia School of Computer Science and Technology Beijing University of Posts and Telecommunications Beijing 100876 China School of Electrical Engineering and Automation Henan Polytechnic University Jiaozuo Henan 454000 China

This paper deals with the iterative learning control （ILC） design for multiple-input multiple-output （MIMO）,time-delay systems （TDS）.Two feedback ILC schemes are considered using the so-called two-dimensional （2D） analysis *** shows that continuous-discrete 2D Roesser systems can be developed to describe the entire learning dynamics of both ILC schemes,based on which necessary and sufficient conditions for their stability can be provided.A numerical example is included to validate the theoretical analysis.

关键词： Iterative learning control Time-delay systems 2D analysis approach

来源：评论

学校读者我要写书评

暂无评论

Prediction model of reservoir fluids properties using sensitivity based linear learning method

Prediction model of reservoir fluids properties using sensit...

引用

International Conference on Multimedia Computing and Information Technology, MCIT'2010

作者： Olatunji, Sunday Olusanya Selamat, Ali Raheem, Abdul Azeez Abdul Intelligent Software Engineering Laboratory Faculty of Computer Science and Information Systems University of Technology Malaysia 81310 UTM Skudai Johor Malaysia Centre for Petroleum and Minerals Research Institute King Fahd University of Petroleum and Mineral Dhahran 31261 Saudi Arabia

ISBN: (纸本)9781424470037

This paper presented a new prediction model for Pressure-Volume-Temperature (PVT) properties based on the recently introduced learning algorithm called Sensitivity Based Linear Learning Method (SBLLM) for two-layer feedforward neural networks. PVT properties are very important in the reservoir engineering computations. The accurate determination of these properties such as bubble-point pressure and oil formation volume factor is important in the primary and subsequent development of an oil field. In this work, we develop Sensitivity Based Linear Learning method prediction model for PVT properties using two distinct databases, while comparing forecasting performance, using several kinds of evaluation criteria and quality measures, with neural network and the three common empirical correlations. Empirical results from simulation show that the newly developed SBLLM based model produced promising results and outperforms others, particularly in terms of stability and consistency of prediction. ©2010 IEEE.

关键词： Learning algorithms

来源：评论

学校读者我要写书评

暂无评论

Modeling permeability prediction using extreme learning machines

Modeling permeability prediction using extreme learning mach...

引用

Asia Modelling Symposium 2010: 4th International Conference on Mathematical Modelling and Computer Simulation, AMS2010

作者： Olatunji, Sunday Olusanya Selamat, Ali Abdul Raheem, Abdul Azeez Intelligent Software Engineering Laboratory Faculty of Computer Science and Information Systems Universiti Teknologi Malaysia 81310 UTM Skudai Johor Malaysia Centre for Petroleum and Minerals Research Institute King Fahd University of Petroleum and Mineral Dhahran 31261 Saudi Arabia

ISBN: (纸本)9780769540627

In this work, an extreme learning machine (ELM) has been used in predicting permeability from well logs data have been investigated and a prediction model has been developed. The prediction model has been constructed using industrial reservoir datasets that are collected from a Middle Eastern petroleum reservoir. Prediction accuracy of the model has been evaluated and compared with commonly used artificial neural network and support vector machines (SVM). We have applied an extreme learning machine (ELM) for single-hidden layer feedforward neural networks (SLFNs). As the ELM has the advantage of fast learning speed and good generalization performance. The simulation results have shown a promising prospect for extreme learning machine in the field of reservoir engineering in particular and oil and gas exploration in general, as it outperforms ANN and SVM. © 2010 IEEE.

关键词： Support vector machines

来源：评论

学校读者我要写书评

暂无评论

Prediction model of permeability from well logs using Type-2 Fuzzy Logic Systems

Prediction model of permeability from well logs using Type-2...

引用

15th International Symposium on Artificial Life and Robotics, AROB '10

作者： Olatunji, Sunday Olusanya Selamat, Ali Raheem, Abdul Azeez Abdul Intelligent Software Engineering Laboratory Faculty of Computer Science and Information Systems Universiti Teknologi Malaysia 81310 UTM Skudai Johor Malaysia Centre for Petroleum and Minerals Research Institute King Fahd University of Petroleum and Mineral Dhahran 31261 Saudi Arabia

ISBN: (纸本)9784990288044

In this paper, the viability and capability of using Type-2 Fuzzy Logic Systems as a novel approach for predicting permeability from Well Logs has been investigated and implemented. Type-2 fuzzy logic is powerful in handling uncertainties, including uncertainties in measurements and data used to calibrate the parameters. In the formulation used, the value of a membership function corresponding to a particular permeability value is no longer a crisp value;rather, it is associated with a range of values that can be characterized by a function that reflects the level of uncertainty. In this way, the model will be able to adequately account for all forms of uncertainties associated with predicting permeability from well log data, where uncertainties are very high and the need for stable results are highly desirable. Comparative studies have been carried out to compare the performance of the proposed framework with those earlier used methods, using real industrial reservoir data. Empirical results from simulation show that Type-2 FLS approach outperforms others in general and particularly in the area of stability and ability to handle data in uncertain situations, which are the common characteristics of well logs data. Another unique advantage of the newly proposed model is its ability to generate, in addition to the normal target forecast, prediction intervals as its by-products without extra computational cost. © 2010 ISAROB.

关键词： Membership functions

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：