检索结果-内蒙古大学图书馆

20th International Conference on Process Control (PC)

作者： Belda, Kvetoslav Acad Sci Czech Republic Inst Informat Theory & Automat Dept Adapt Syst Pod Vodarenskou Vezi 4 Prague 8 Czech Republic

ISBN: (纸本)9781467366274

A specific efficient solution of constrained system outputs is presented. The solution is based on on-line weighting of individual system outputs or output components representing in fact a specific on-line tuning/applification of the components of weighting control parameters. Thus, the predictive control design retains flexibility without any increase of time-computational demands. The proposed solution represents only soft solution of the constraints, i.e. a compliance with the constraints is not fully guaranteed, but the result is satisfactory and not so far from results of hard-constraint solution computed e.g. by a quadratic programming. The solution predetermines the area of the use to the systems with fast dynamics requiring very high sampling rates as electric drives and the like. The solution is presented in the paper as a generalized solution for common use. It is demonstrated by simple simulative examples and one illustration from a real control of 3-phase electric drive.

关键词： Predictive control incremental algorithms system constraints component tuning of control parameters quadratic cost function quadratic programming problem

来源：评论

学校读者我要写书评

暂无评论

incremental Detection of Inconsistencies in Distributed Data

引用

IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING 2014年第6期26卷 1367-1383页

作者： Fan, Wenfei Li, Jianzhong Tang, Nan Yu, Wenyuan Univ Edinburgh Sch Informat Lab Fdn Comp Sci LFCS Edinburgh EH8 9AB Midlothian Scotland Harbin Inst Technol Sch Comp Sci & Technol Dept Comp Sci & Engn Heilongjiang 150001 Peoples R China Qatar Fdn Qatar Comp Res Inst QCRI Doha Qatar

This paper investigates incremental detection of errors in distributed data. Given a distributed database D, a set Sigma of conditional functional dependencies (CFDs), the set V of violations of the CFDs in D, and updates Delta D to D, it is to find, with minimum data shipment, changes Delta V to V in response to Delta D. The need for the study is evident since real-life data is often dirty, distributed and frequently updated. It is often prohibitively expensive to recompute the entire set of violations when D is updated. We show that the incremental detection problem is NP-complete for database D that is partitioned either vertically or horizontally, even when Sigma and D are fixed. Nevertheless, we show that it is bounded: there exist algorithms to detect errors such that their computational cost and data shipment are both linear in the size of Delta D and Delta V, independent of the size of the database D. We provide such incremental algorithms for vertically partitioned data and horizontally partitioned data, and show that the algorithms are optimal. We further propose optimization techniques for the incremental algorithm over vertical partitions to reduce data shipment. We verify experimentally, using real-life data on Amazon Elastic Compute Cloud (EC2), that our algorithms substantially outperform their batch counterparts.

关键词： incremental algorithms distributed data conditional functional dependencies error detection

来源：评论

学校读者我要写书评

暂无评论

Speeding up incremental wrapper feature subset selection with Naive Bayes classifier

引用

KNOWLEDGE-BASED SYSTEMS 2014年 55卷 140-147页

作者： Bermejo, Pablo Gamez, Jose A. Puerta, Jose M. Univ Castilla La Mancha Intelligent Syst & Data Min Lab 13A Dept Comp Syst Albacete 02071 Spain

This paper deals with the problem of wrapper feature subset selection (FSS) in classification-oriented datasets with a (very) large number of attributes. In high-dimensional datasets with thousands of variables, wrapper FSS becomes a laborious computational process because of the amount of CPU time it requires. In this paper we study how under certain circumstances the wrapper FSS process can be speeded up by embedding the classifier into the wrapper algorithm, instead of dealing with it as a black-box. Our proposal is based on the combination of the NB classifier (which is known to be largely beneficial for FSS) with incremental wrapper FSS algorithms. The merit of this approach is analyzed both theoretically and experimentally, and the results show an impressive speed-up for the embedded FSS process. (C) 2013 Elsevier B.V. All rights reserved.

关键词： Wrapper feature subset selection incremental algorithms Naive Bayes High-dimensional data

来源：评论

学校读者我要写书评

暂无评论

The incremental Maintenance of Transition Tour

引用

FUNDAMENTA INFORMATICAE 2014年第3期129卷 279-300页

作者： Nemeth, Gabor Arpad Pap, Zoltan Budapest Univ Technol & Econ Dept Telecommun & Media Informat High Speed Networks Lab H-1117 Budapest Hungary

While evolutionary development methodologies have become increasingly prevalent, incremental testing methods are lagging behind. Most traditional test generation algorithms-including the Transition Tour method-rebuild test sequences from scratch even if minimal changes to the system have been made. In the current paper we propose two incremental algorithms to update a Transition Tour test sequence after changes in a deterministic finite state machine model. Our solution uses existing information-the Eulerian graph of a previous version of the system and an Euler tour in it-to update the test cases of the system in response to modification. The first algorithm keeps an Eulerian graph up to date, while the second algorithm maintains an Euler tour in the augmented graph. Analytical and practical analyses show that our algorithms are very efficient in the case of changing specifications. We also demonstrate our methods through an example.

关键词： finite state machine test generation algorithms incremental algorithms incremental test generation

来源：评论

学校读者我要写书评

暂无评论

An incremental algorithm for updating betweenness centrality and k-betweenness centrality and its performance on realistic dynamic social network data

引用

SOCIAL NETWORK ANALYSIS AND MINING 2014年第1期4卷 1-23页

作者： Kas, Miray Carley, Kathleen M. Carley, L. Richard Carnegie Mellon Univ Ctr Computat Anal Social & Org Syst CASOS Pittsburgh PA 15213 USA

The increasing availability of dynamically changing digital data that can be used for extracting social networks over time has led to an upsurge of interest in the analysis of dynamic social networks. One key aspect of dynamic social network analysis is finding the central nodes in a network. However, dynamic calculation of centrality values for rapidly changing networks can be computationally expensive, with the result that data are frequently aggregated over many time periods and only intermittently analyzed for centrality measures. This paper presents an incremental betweenness centrality algorithm that efficiently updates betweenness centralities or k-betweenness centralities of nodes in dynamic social networks by avoiding re-computations through the efficient storage of information from earlier computations. In this paper, we evaluate the performance of the proposed algorithms for incremental betweenness centrality and k-betweenness centrality on both synthetic social network data sets and on several real-world social network data sets. The presented incremental algorithm can achieve substantial performance speedup (3-4 orders of magnitude faster for some data sets) when compared to the state of the art. And, incremental k-betweenness centrality, which is a good predictor of betweenness centrality, can be carried out on social network data sets with millions of nodes.

关键词： Betweenness centrality k-Betweenness centrality incremental algorithms Dynamic network analysis All-pairs shortest paths

来源：评论

学校读者我要写书评

暂无评论

incremental FUZZY CLUSTERING WITH MULTIPLE KERNELS

INCREMENTAL FUZZY CLUSTERING WITH MULTIPLE KERNELS

引用

1st International Conference on Advanced Technologies for Signal and Image Processing (ATSIP)

作者： Baili, Naouel Frigui, Hichem Univ Louisville Louisville KY 40292 USA

ISBN: (纸本)9781479948888

This paper presents two incremental clustering algorithms based on FCMK, a fuzzy clustering with multiple kernels algorithm we developed earlier [1]. The FCMK algorithm has a memory requirement of O(N-2), where N is the number of objects in the data set. Thus, even data sets that have nearly 1, 000, 000 objects require terabytes of working memory-impractical for most computers. One way to attack this problem is by using incremental algorithms;these algorithms sequentially process chunks or samples of the data, combining the results from each chunk. The proposed incremental algorithms neither use any complicated data structure nor any complicated data compression techniques, yet produce data partitions comparable to FCMK. We assess the performance of our incremental algorithms by, first, comparing their clustering results to that of the FCMK and, second, by showing that these algorithms can produce reasonable partitions of large data sets.

关键词： Fuzzy clustering multiple kernels incremental algorithms

来源：评论

学校读者我要写书评

暂无评论

The furthest neighbor query of space K

The furthest neighbor query of space K

引用

International Conference on Wavelet Analysis and Pattern Recognition (ICWAPR)

作者： Cheng Chang Run-Tao Liu Department of applied mathematics Harbin University of Science and Technology Institute of information and scientific computing technology Harbin University of Science and Technology

ISBN: (纸本)9781467372251

In the spatial database, the furthest neighbor query is a jumped-up method. If different distances and pruning strategies are properly selected, we can greatly reduce the node number in search space. Through using data cube and edge detection method, we catch up with the traverse pruning method that is based on FNC spatial index tree of incremental and query algorithms. The experimental result turns out that the algorithms have a good pruning effect, at the same time promoting the query efficiency of space k farthest neighbors.

关键词： database indexing edge detection query processing search problems trees (mathematics) visual databases FNC spatial index tree data cube edge detection method furthest neighbor query incremental algorithms jumped-up method node number pruning effect pruning strategies query algorithms query efficiency search space space k farthest neighbors spatial database traverse pruning method FNC-Tree Spatial databases Sub cube The furthest neighbor query visual databases boundary detection algorithm database indexing tabu search query analysis Edge detection data cubes Neighbor

来源：评论

学校读者我要写书评

暂无评论

Adaptive training set reduction for nearest neighbor classification

引用

NEUROCOMPUTING 2014年 138卷 316-324页

作者： Ramon Rico-Juan, Juan Inesta, Jose M. Univ Alicante Dpto Lenguajes & Sistemas Informat E-03081 Alicante Spain

The research community related to the human-interaction framework is becoming increasingly more interested in interactive pattern recognition, taking direct advantage of the feedback information provided by the user in each interaction step in order to improve raw performance. The application of this scheme requires learning techniques that are able to adaptively re-train the system and tune it to user behavior and the specific task considered. Traditional static editing methods filter the training set by applying certain rules in order to eliminate outliers or maintain those prototypes that can be beneficial in classification. This paper presents two new adaptive rank methods for selecting the best prototypes from a training set in order to establish its size according to an external parameter that controls the adaptation process, while maintaining the classification accuracy. These methods estimate the probability of each prototype of correctly classifying a new sample. This probability is used to sort the training set by relevance in classification. The results show that the proposed methods are able to maintain the error rate while reducing the size of the training set, thus allowing new examples to be learned with a few extra computations. (C) 2014 Elsevier B.V. All rights reserved.

关键词： Editing Condensing Rank methods Sorted prototypes selection Adaptive pattern recognition incremental algorithms

来源：评论

学校读者我要写书评

暂无评论

Theory and Practice in Large Carpooling Problems

Theory and Practice in Large Carpooling Problems

引用

5th International Conference on Ambient Systems, Networks and Technologies (ANT) / 4th International Conference on Sustainable Energy Information Technology (SEIT)

作者： Hartman, Irith Ben-Arroyo Keren, Daniel Abu Dbai, Abed Cohen, Elad Knapen, Luk Yasar, Ansar-Ul-Haque Janssens, Davy Univ Haifa Dept Comp Sci IL-3498838 Haifa Israel Univ Haifa Caesarea Rothschild Inst IL-3498838 Haifa Israel Hasselt Univ Transportat Res Inst IMOB B-3950 Diepenbeek Belgium

We address the carpooling problem as a graph-theoretic problem. If the set of drivers is known in advance, then for any car capacity, the problem is equivalent to the assignment problem in bipartite graphs. Otherwise, when we do not know in advance who will drive their vehicle and who will be a passenger, the problem is NP-hard. We devise and implement quick heuristics for both cases, based on graph algorithms, as well as parallel algorithms based on geometric/algebraic approach. We compare between the algorithms on random graphs, as well as on real, very large, data. (C) 2014 Published by Elsevier B.V.

关键词： Carpooling Linear Programming Maximum Weighted Matching Star Partition Problem Gradient Projection Algorithm Scalability incremental algorithms

来源：评论

学校读者我要写书评

暂无评论

Theory and Practice in Large Carpooling Problems

引用

Procedia Computer Science 2014年 32卷 339-347页

作者： Irith Ben-Arroyo Hartman Daniel Keren Abed Abu Dbai Elad Cohen Luk Knapen Ansar-Ul-Haque Yasar Davy Janssens Department of Computer Science University of Haifa Haifa 3498838 Israel Caesarea Rothschild Institute University of Haifa Haifa 3498838 Israel Transportation Research Institute(IMOB) Hasselt University Wetenschapspark 5 B3950 Diepenbeek Belgium

关键词： Carpooling Linear Programming Maximum Weighted Matching Star Partition Problem Gradient Projection Algorithm Scalability incremental algorithms

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：