检索结果-内蒙古大学图书馆

26th International Conference On Machine Learning, ICML 2009

作者： Busetto, Alberto Giovanni Ong, Cheng Soon Buhmann, Joachim M. Department of Computer Science ETH Zurich Universitätstr. 6 8092 Zurich Switzerland Competence Center for Systems Physiology and Metabolic Diseases Schafmattst. 18 8093 Zurich Switzerland Life Science Zurich PhD Program on Systems Biology of Complex Diseases Switzerland

ISBN: (纸本)9781605585161

This paper addresses the problem of active model selection for nonlinear dynamical systems. We propose a novel learning approach that selects the most informative subset of time-dependent variables for the purpose of Bayesian model inference. The model selection criterion maximizes the expected Kullback-Leibler divergence between the prior and the posterior probabilities over the models. The proposed strategy generalizes the standard D-optimal design, which is obtained from a uniform prior with Gaussian noise. In addition, our approach allows us to determine an information halting criterion for model identification. We illustrate the benefits of our approach by differentiating between 18 published biochemical models of the TOR signaling pathway, a model selection problem in systems biology. By generating pivotal selection experiments, our strategy outperforms the standard A-optimal, D-optimal and E-optimal sequential design techniques.

关键词： Nonlinear dynamical systems

来源：评论

学校读者我要写书评

暂无评论

A machine learning technique to detect and predict parkinson's disease

A machine learning technique to detect and predict parkinson...

引用

2009 International Conference on Image Processing, computer Vision, and Pattern Recognition, IPCV 2009

作者： Yuan, Peijiang Zhang, Bo Li, Jianmin Wang, Julei Gao, Guodong State Key Laboratory of Intelligent Technology and Systems Department of Computer Science and Technology Tsinghua University Beijing 100084 China TangDu Hospital Institute of Functional Brain Disorders Fourth Military Medical University Xi'an China

ISBN: (纸本)9781601321190

Parkinson's Disease (PD) is a neurological disorder that has been a hot topic worldwide. Human neurological disorders can be modeled in animals like rats and monkeys using standardized procedures that recreate specific pathogenic events and their behavioral outcomes. Different methods have been proposed to detect and verify the efficiency and effectiveness of such models. However, the inner scheme to detect and predict PD at the early stage is still a difficult problem. In this paper, a Conditional Random Fields (CRFs) based approach for PD image detection and prediction is presented. Machine learning techniques are discussed that proved to be useful in detecting and predicting PD in animal models.

关键词： Animals

来源：评论

学校读者我要写书评

暂无评论

Load forecasting of a desert: A computational intelligence approach

Load forecasting of a desert: A computational intelligence a...

引用

2009 15th International Conference on intelligent System Applications to Power systems, ISAP '09

作者： Saber, Ahmed Yousuf Al-Shareef, Abdulaziz Real-Time Power and Intelligent Systems Laboratory Missouri University of Science and Technology Rolla MO 65409-0040 United States Electrical and Computer Engineering Department King Abdulaziz University Jeddah KSA Saudi Arabia

ISBN: (纸本)9781424450985

This paper presents artificial neural networks and particle swarm optimization (ANN-PSO) based short-term load forecasting model with improved generalization technique for the Regional Power Control Center of Saudi Electricity Company, Western Operation Area (SEC-WOA) of Saudi Arabia. Weather, load demand, wind speed, wind direction, heat, sunlight, etc. are quite different in a desert land than other places. Thus this model is different from a typical forecasting model considering inputs and outputs. In this research, two models are implemented - firstly load forecasting model for prediction;however, it is not sufficient for desired level of accurate forecasting, and secondly, optimization to improve the results up to at least better than existing results. This paper includes ANN and PSO models for 24-hours ahead load forecasting. ANN is a mathematical tool for mapping complex relations;it is well proved for the successful use of prediction, function approximation with dynamics, categorization, classification, and so forth. In this research, 24- step ahead calculations are performed in the ANN model and results are moderate. On the other hand, PSO is the most promising optimization tool. It is a swarmed based optimization method;it has better information sharing and conveying mechanism;it has better balance of local and global searching abilities;it can handle huge multi-dimensional optimization problems efficiently with hundreds of thousands of constraints. Thus PSO is chosen as the optimization tool that is applied on the weight matrix of ANN to improve results. In this research, PSO reliably and accurately tracks the continuously changing weights of ANN for uncertain load demand. By analyzing the model of ANN for the load-forecasting problem of SEC-WOA with hundreds of thousands of data and changing-uncertain load demand, the PSO is applied for the ANN weight adjustment and to optimize the uncertain load demand, as the ANN is not an optimization method. Results

关键词： Neural networks

来源：评论

学校读者我要写书评

暂无评论

Social and Behavioral Aspects of a Tag-Based Recommender System

Social and Behavioral Aspects of a Tag-Based Recommender Sys...

引用

International Conference on intelligent systems Design and Applications (ISDA)

作者： Frederico Durao Peter Dolog IWIS-Intelligent Web and Information Systems Computer Science Department University of Aalborg Aalborg Denmark

Collaborative tagging has emerged as a useful means to organize and share resources on the Web. Recommender systems have been utilized tags for identifying similar resources and generate personalized recommendations. In this paper, we analyze social and behavioral aspects of a tag-based recommender system which suggests similar Web pages based on the similarity of their tags. Tagging behavior and language anomalies in tagging activities are some aspects examined from an experiment involving 38 people from 12 countries.

关键词： Recommender systems Tagging Web pages Information systems computer science Collaborative work Ontologies Cultural differences intelligent systems Application software

来源：评论

学校读者我要写书评

暂无评论

Multi-Layer Audio Watermarking Based on Amplitude Modification

Multi-Layer Audio Watermarking Based on Amplitude Modificati...

引用

International Conference on intelligent Information Hiding and Multimedia Signal Processing (IIHMSP)

作者： Akio Ogihara Harumi Murata Motoi Iwata Akira Shiozaki Department of Computer Science and Intelligent Systems Graduate School of Engineering Osaka Prefecture University Japan

In the conventional method proposed by *** et al., it is difficult to satisfy both the capacity of watermark information and the robustness to MP3 compression. The objective of this work is to increase the capacity of watermark information in the audio watermarking based on low-frequency amplitude modification. We increase the capacity of watermark information by embedding multiple watermarks in individual layers. In the proposed method, it has plural data channels, so it is possible to embed watermark information by selecting the proper data channel according to the capacity of data or extraction accuracy.

关键词： Watermarking Data mining Digital audio players Robustness Multimedia systems Signal processing computer science intelligent systems Internet Digital filters

来源：评论

学校读者我要写书评

暂无评论

Matchmaking Using Natural Language Descriptions: Linking Customers with Enterprise Service Descriptions

Matchmaking Using Natural Language Descriptions: Linking Cus...

引用

IEEE Annual International computer Software and Applications Conference (COMPSAC)

作者： Joe Geldart William Song Yang Li Department of Computer Science University of Durham Durham UK Intelligent Systems Research Center UK

ISBN: (纸本)9781424445257

A novel architecture is presented for the matching of Web-services based on the extraction of interpretation graphs from natural language text. The graphs of candidate services are compared to that of the query using a numerical node-node similarity calculation based on the structure of the graphs. The similarity score of their best alignment with the query may then be used to rank the candidates.

关键词： Natural languages Joining processes Software libraries programmable control Humans Formal languages Context modeling Software quality Logic Quality of service

来源：评论

学校读者我要写书评

暂无评论

PSF-constraints based iterative blind deconvolution method for image deblurring

PSF-constraints based iterative blind deconvolution method f...

引用

16th International Multimedia Modeling Conference on Advances in Multimedia Modeling, MMM 2010

作者： Mo, Xuan Jiao, Jun Shen, Chen Department of Automation State Key Laboratory of Intelligent Technology and Systems Tsinghua University Beijing China Dept. of Computer Science and Technology Nanjing University Nanjing China School of Software and Electronics Peking University Beijing China

ISBN: (纸本)3642113001

In recent years, Image Deblurring techniques have played an essential role in the field of Image Processing. In image deblurring, there are several kinds of blurred image such as motion blur, defocused blur and gaussian blur. Many methods to address this problem have been proposed by researchers in previous research, among which the iterative blind deconvolution (IBD) method is the most popular method to solve this problem. However, the convergence of this method is not ensured, and there is no effective method to choose a proper initial estimate image and PSF(point spread function). In this paper, we improve the iterative blind deconvolution method by adding several constraints, which could be the type or parameters range of the PSF, on the PSF in each iteration. Experiment results validate that, with the help of these newly added constraints, our method are more likely to converge and has better deblurring performance than the IBD. © 2010 Springer-Verlag Berlin Heidelberg.

关键词： Optical transfer function

来源：评论

学校读者我要写书评

暂无评论

Illumination Invariant Object Tracking with Incremental Subspace Learning

Illumination Invariant Object Tracking with Incremental Subs...

引用

International Conference on Image and Graphics (ICIG)

作者： Gang Yu Hongtao Lu MOE-Microsoft Laboratory of Intelligent Computing and Intelligent Systems Department of Computer Science and Engineering Shanghai JiaoTong University Shanghai China

ISBN: (纸本)9781424452378

In this paper, we present an efficient and robust subspace learning based object tracking algorithm with special illumination handling. Illumination variances pose a great challenge to most of object tracking algorithms. In this paper, an edge orientation based feature has been proposed and proven to approximately invariant to illumination changes. Besides, we utilize the incremental subspace learning based particle filter framework which is effective to handle various appearance changes. To reduce the amount of computation when the particle number is large, a new layer of preprocessing step has been added to the particle filter framework with the help of edge orientation features. From the experimental m results, it is obvious that our proposed algorithm achieves promising performance especially in the scenarios with large illumination changes.

关键词： Lighting Target tracking Stochastic processes Particle filters Iterative algorithms Optimization methods Stochastic resonance Noise robustness computer graphics Laboratories

来源：评论

学校读者我要写书评

暂无评论

Chinese lexical analysis based on hidden semi-crf

引用

ICIC Express Letters 2009年第2期3卷 177-182页

作者： Sun, Xiao Huang, Degen Ren, Fuji Department of Computer Science and Engineering Dalian University of Technology Liaoning 116023 China Department of Information Science and Intelligent Systems University of Tokushima Tokushima 7708506 Japan

In order to solve problems of the Chinese word segmentation and POS tagging which are still existing in Chinese lexical analysis, a Hidden semi-CRF model, which has two chains of states with unequal number of states, is proposed for the Chinese lexical analysis. The Hidden semi-CRF detects the words together with their part-of-speech regardless whether the words are in the system dictionary or not. A new-words-generating framework is also built for training and testing, under which the definition and distribution of the new words conforms to the characteristic of the ones in real text. The proposed framework enhances the performance ofnew words detecting and POS tagging, so that the overall precision of the system for Chinese lexical analysis could be further increased. The experiment results show that the proposed method is capable of detecting even low frequency new words, which in return increases the overall precision of Chinese word segmentation and POS tagging in Chinese lexical analysis. © 2009 ISSN.

关键词： Computational linguistics

来源：评论

学校读者我要写书评

暂无评论

Generating single granularity-based fuzzy classification rules for multiobjective genetic fuzzy rule selection

Generating single granularity-based fuzzy classification rul...

引用

IEEE International Conference on Fuzzy systems (FUZZ-IEEE)

作者： Rafael Alcala Yusuke Nojima Francisco Herrera Hisao Ishibuchi Department of Computer Science and A.I. University of Granada Granada Spain Department of Computer Science and Intelligent Systems Osaka Prefecture University Sakai Osaka Japan

Recently, multiobjective evolutionary algorithms have been applied to improve the difficult tradeoff between interpretability and accuracy of fuzzy rule-based systems. It is known that both requirements are usually contradictory, however, these kinds of algorithms can obtain a set of solutions with different trade-offs. The application of multiobjective evolutionary algorithms to fuzzy rule-based systems is often referred to as multiobjective genetic fuzzy systems. The first study on multiobjective genetic fuzzy systems was multiobjective genetic fuzzy rule selection in order to simultaneously achieve accuracy maximization and complexity minimization. This approach is based on the generation of a set of candidate fuzzy classification rules by considering a previously fixed granularity or multiple fuzzy partitions with different granularities for each attribute. Then, a multiobjective evolutionary optimization algorithm is applied to perform fuzzy rule selection. Although the multiple granularity approach is one of the most promising approaches, its interpretability loss has often been pointed out. In this work, we propose a mechanism to generate single granularity-based fuzzy classification rules for multiobjective genetic fuzzy rule selection. This mechanism is able to specify appropriate single granularities for fuzzy rule extraction before performing multiobjective genetic fuzzy rule selection. The results show that the performance of the obtained classifiers can be even improved by avoiding multiple granularities, which increases the linguistic interpretability of the obtained models.

关键词： Genetics Fuzzy systems Knowledge based systems Fuzzy sets Evolutionary computation Partitioning algorithms Data mining Fuzzy logic computer science intelligent systems

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：