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检索条件"机构=Key Laboratory of Intelligent Information Perception and Processing Technology"

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The Implement Approach of Product Optimization for Variant Design Based on the Artificial Immune Algorithm

The Implement Approach of Product Optimization for Variant D...

引用

International Conference on Innovative Computing, information and Control (ICICIC)

作者： Xiuyan Zhao Xiaopeng Wei Tingting Zhao Qiang Zhang Liaoning Key Laboratory of Intelligent Information Processing Dalian University of Technology Dalian China

According to the requirement of rapid variant design for products, it is vital that the complicated problem is transformed into the optimization problem. On the basis of it, an effective product optimization model of variant design is established. An improved artificial immune algorithm is adopted, which simulates the protein polypeptide structure of the antibody, the clone selection principle and the concentration regulation of the immune system, and uses a new analytic approach for the similarity between the antibodies. Finally, an example is given to evaluate the performance of the proposed approach. The simulation results illustrate the effectiveness of the proposed method in variant design of products.

关键词： Optimization Algorithm design and analysis Cloning Mathematical model Correlation Artificial neural networks Mathematics

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A Bee Swarm Genetic Algorithm for the Optimization of DNA Encoding

A Bee Swarm Genetic Algorithm for the Optimization of DNA En...

引用

International Conference on Innovative Computing, information and Control (ICICIC)

作者： Chunxia Xu Qiang Zhang Jinsong Li Xiuyan Zhao Liaoning Key Laboratory of Intelligent Information Processing Dalian University of Technology Dalian China

ISBN: (纸本)9781424431977;9780769531618

Bee Swarm Genetic Algorithm (BSGA), a new efficient algorithm is developed for designing DNA sequences that satisfy some combinatorial and thermodynamic constraints. In BSGA, the optimum individual of population selected as a queen bee and a random population is introduced to reinforce the exploitation of Genetic Algorithm (GA) and increase the diversity of population. Based on the algorithm, a computer simulation for DNA encoding is conducted and the sequences are better than the previous known systems that can prove the efficiency and convergence of our algorithm.

关键词： DNA Encoding Genetic algorithms DNA computing Hamming distance Algorithm design and analysis Convergence

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Spectral Correlation-Based Multi-Antenna Spectrum Sensing Technique

Spectral Correlation-Based Multi-Antenna Spectrum Sensing Te...

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IEEE Conference on Wireless Communications and Networking

作者： Xing Chen Wenjun Xu Zhiqiang He Xiaofeng Tao Key Laboratory of Information Processing and Intelligent Technology Beijing China Key Laboratory of Universal Wireless Communications Beijing China

To meet the challenges in sensing the spectrum in a reliable and timely manner, an approach of multi-antenna spectrum sensing based on spectral correlation property is proposed in this paper. Without any prior information of the licensed system, it extracts the frequency-domain channel information from the spectral correlation functions (SCF) of multiple antenna signals, and then generates the SCF of multi-antenna combining (SCF-MAC) over the frequency-cycle frequency plane. The expressions for the detection and false alarm probabilities of a decision based on SCF-MAC are derived for frequency selective channel, which indicate the proposed approach is capable of achieving full spatial diversity in spectrum sensing. Simulation results corroborate the theoretical analysis and show the significant performance improvement.

关键词： Diversity reception Chromium Laboratories Analytical models Performance analysis Fading Centralized control Radio control Frequency estimation Frequency domain analysis

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Ontology-Based Deep Web Synchronous-Annotation

Ontology-Based Deep Web Synchronous-Annotation

引用

ISECS International Colloquium on Computing, Communication, Control, and Management, CCCM

作者： PengYu Hu Wei Fang ZhiMing Cui Jiangsu Provincial Key Laboratory of Computer Information Processing Technology The Institute of Intelligent Information Processing and Application Soochow University Suzhou China

An increasing number of databases have become Web accessible through HTML form-based search interfaces, which is so-called deep Web. For full utilization of deep Web resources and improving Web intelligence, which is essential for many applications such as deep Web data collection and comparison shopping, they need to be extracted out and assigned meaningful labels. In this paper, we present a synchronous-annotation approach that introduce domain ontology as a global schema ordered by Web databases to the annotation process. We combine ontology, interface schema and result schema and adopt the strategy of query ontology instance to implement annotation. In order to verify the effectiveness of the method proposed in this paper, we test on a number of different areas of Web databases. The experimental results indicate that the proposed approach is more effective than existing approaches.

关键词： Ontologies Databases Vocabulary Data mining Books Music Motion pictures

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From Wrapping to Knowledge: Domain Ontology Learning from Deep Web

From Wrapping to Knowledge: Domain Ontology Learning from De...

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International Symposiums on information processing (ISIP)

作者： Zhiming Cui Pengpeng Zhao Wei Fang Chao Lin The Institute of Intelligent Information Processing and Application China Jiangsu Key Laboratory of Computer Information Processing Technology Soochow University Suzhou China

ISBN: (纸本)9781424430536;9780769531519

The next generation of the Web, called Semantic Web, has to improve the Web with semantic page annotations to enable knowledge-level querying and searches. However, manual construction of these ontologies is a time consuming and difficult task. In this paper, we describe an automatic extraction method that learns domain ontologies for semantic web from deep web. Our approach first learns a base ontology from deep web query interfaces, then grows the current ontology by probing the sources and discovering additional concepts and instances from the result pages. We have evaluated our approach in several real-world domains. Preliminary results indicate that the proposed extraction method discovers concepts and instances with high accuracy.

关键词： Wrapping Ontologies Semantic Web information processing Databases Knowledge engineering Chaos Application software Laboratories Machine learning

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A hierarchical framework for movie content analysis: Let computers watch films like humans

A hierarchical framework for movie content analysis: Let com...

引用

2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, CVPR Workshops

作者： Anan, Liu Sheng, Tang Yongdong, Zhang Yan, Song Jintao, Li Zhaoxuan, Yang Virtual Reality Laboratory Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China Department of Electronic Engineering Tianjin University Tianjin 300072 China

ISBN: (纸本)9781424423408

In this paper, we specially propose a hierarchical framework for movie content analysis. The purpose of our work is trying to realize computers' understanding for movie content, especially "Who, What, Where, How" which occur in the storyline by imitating human perception and cognition. The framework consists of two hierarchies. As for the low level part, we originally construct the human attention model with temporal information motivated by the Weber-Fechner Law to depict the variation of human perception in multiple modalities. As for the high level part, we focus on semantic understanding of different granularities of videos and simulate human cognition for movie content. Based on this hierarchical framework, we present its applications on semantic retrieval, video summarization and content filter. The promising results of users' subjective assessment indicate that the proposed framework is applicable for automatic analysis of movie content by computers. © 2008 IEEE.

关键词： Semantics

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Optimal Power Control Game Algorithm for Cognitive Radio Networks with Multiple Interference Temperature Limits

Optimal Power Control Game Algorithm for Cognitive Radio Net...

引用

IEEE Conference on Vehicular technology (VTC)

作者： Hongyan Li Yibing Gai Zhiqiang He Kai Niu Weiling Wu Key Laboratory of Information Processing and Intelligent Technology Beijing University of Posts and Telecommunications Beijing China

Based on interference temperature model, the problem of secondary spectrum sharing can be formulated as a power optimization problem at physical layer. In this paper, we consider decentralized cognitive radio networks, and we especially focus on the spectrum sharing scenario where multiple measurement points are located in the licensed system. Game theory is used to investigate the distributed power control for providing the maximum throughput in cognitive radio networks. There are two aspects that should be considered in the design of the payoff function for each player, one is counteracting negative externalities in cognitive radio networks, and the other is satisfying all the interference temperature limits from measurement points. A tax-based power control game algorithm is introduced to implement power allocation optimization in a distributed mode, and guarantees the convergence to globally optimal power allocations.

关键词： Power control Cognitive radio Interference Power system modeling Temperature sensors Chromium Physical layer Game theory Throughput Temperature measurement

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The Data Selection Criteria for HSC and SVM Algorithms

The Data Selection Criteria for HSC and SVM Algorithms

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International Conference on Natural Computation (ICNC)

作者： Qing He Fuzhen Zhuang Zhongzhi Shi The Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences China

This paper makes a discussion of consistent subsets (CS) selection criteria for hyper surface Classification (HSC) and SVM algorithms. The consistent subsets play an important role in the data selection. Firstly, the paper proposes that minimal consistent subset for a disjoint cover set (MCSC) plays an important role in the data selection for HSC. The MCSC can be applied to select a representative subset from the original sample set for HSC. MCSC has the same classification model with the entire sample set and can totally reflect its classification ability. Secondly, the number of MCSC is calculated. Thirdly, by comparing the performance of HSC and SVM on corresponding CS, we argue that it is not reasonable that using the same train data set to train different classifiers and then testing the classifiers by the same test data set for different algorithms. The experiments show that algorithms can respectively select the proper data set for training, which ensures good performance and generalization ability. MCSC is the best selection for HSC, and support vector set is the effective selection for SVM.

关键词： Support vector machines Support vector machine classification Nearest neighbor searches Neural networks Testing Laboratories information processing Computers Helium Databases

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A Relevance Feedback Image Retrieval Approach Based on RGA

A Relevance Feedback Image Retrieval Approach Based on RGA

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International Symposium on Knowledge Acquisition and Modeling, KAM

作者： Quanzhong Liu Jijun Wang Guojie Feng Zifang Zhang Liaoning Key Laboratory of Intelligent Information Processing Dalian University of Technology Dalian Liaoning China

Relevance Feedback is one of the key technologies of Content-Based Image Retrieval, which has an important impact on performance of retrieval. Give a Relevance Feedback image retrieval approach based on RGA. Introduce the relevant technologies and evaluation methods of Relevance Feedback. Expound the design of fitness function and genetic operator of real-code Genetic Algorithm. As show as the experiment, the methods improve the performance of retrieval, good results can be obtained.

关键词： Feedback Image retrieval information retrieval Radio frequency Content based retrieval Genetic algorithms Humans Image databases Knowledge acquisition Laboratories

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A New Algorithm for Mixture Splitting Based on DBC

A New Algorithm for Mixture Splitting Based on DBC

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International Symposium on intelligent information technology Application, IITA

作者： Gang Liu Wei Chen Jun Guo Key Laboratory of Information Processing and Intelligent Technology Beijing University of Posts and Telecommunications Beijing China

EM (expectation-maximization) algorithm is a classical method for parameter estimation of HMM (Hidden Markov model ). Concerning that EM algorithm is easily affected by initial parameter values, we proposed a mixture splitting algorithm based on decision boundary confusion (DBC) to describe more about boundary distribution. The algorithm mainly includes three aspects: firstly the number of incremented mixtures for every decision boundary could be determined according to decision boundary confusion; secondly the mixtures which are the closest to the decision boundary are chosen to split, thirdly the split mean of mixture is in the direction of decision boundary. Our experiments show that our proposed algorithm is more effective for classification using HMM.

关键词： Hidden Markov models Iterative algorithms Parameter estimation Maximum likelihood estimation information technology Laboratories information processing Pattern recognition Training data Probability distribution

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