检索结果-内蒙古大学图书馆

International Conference on Computer Engineering and Technology, ICCET

作者： Jianwei Liang Haifeng You Xufa Wang Department of Computer Science and Technology Anhui Key Laboratory of Software in Computing and Communication University of Science and Technology Hefei China

This article has been retracted by the publisher.

关键词：

来源：评论

学校读者我要写书评

暂无评论

A Clustering System for Gene Expression Data Based upon Genetic Programming and the HS-Model

A Clustering System for Gene Expression Data Based upon Gene...

引用

The Third International Joint Conference on computational Science and Optimization(第三届计算科学与优化国际大会 CSO 2010)

作者： Guiquan Liu Xiufang Jiang Lingyun Wen Key Laboratory of Software in Computing and Communication Anhui Province School of Computer Science and Technology University of Science and Technology of China Hefei Anhui 230027 China

ISBN: (纸本)9781424468126;9780769540306

Cluster analysis is a major method to study gene function and gene regulation information for there is a lack of prior knowledge for gene data. Many clustering methods existed at present usually need manual operations or predetermined parameters, which are difficult for gene data. Besides, gene data possess their own characteristics, such as large scale, high-dimension, and noise. Therefore, a systematic clustering algorithm should be proposed to effectively deal with gene data. In this paper, a novel genetic programming (GP) clustering system for gene data based on hierarchical statistical model (HS-model) is proposed. And an appropriate fitness function is also proposed in this system. This clustering system can largely eliminate the infection of data scale and dimension. The proposed GP clustering system is applied to cluster the whole intact yeast gene data without dimensionality reduction. The experimental results indicate that the algorithm is highly efficient and can effectively deal with missing values in gene dataset

关键词： genetic programming cluster analysis missing value fitness function

来源：评论

学校读者我要写书评

暂无评论

A fast algorithm for finding community structure based on community closeness

A fast algorithm for finding community structure based on co...

引用

The Third International Joint Conference on computational Science and Optimization(第三届计算科学与优化国际大会 CSO 2010)

作者： Xiufang Jiang Guiquan Liu Zhiting Lin Key Laboratory of Software in Computing and Communication Anhui Province School of Computer Science and Technology University of Science and Technology of China Hefei Anhui 230027 China

ISBN: (纸本)9781424468126;9780769540306

Recently, the characterization of community structures in complex networks has received a considerable amount of attentions. Effective identification of these communities or clusters is a general problem in the field of data mining. In this paper we present a /ast hierarchical agglomerative algorithm based on community closeness (FHACC) algorithm, for detecting community structure which is very efficient and faster than many other competing algorithms. FHACC tends to agglomerate such communities that share the most common vertices into larger ones. Its running time on a sparse network with n vertices and m edges is O(mk + mt), where k denotes the mean vertex degree, and t is the iteration times of community agglomeration in FHACC algorithm. The algorithm was tested on several real-world networks and proved to be high efficient and effective in community finding.

关键词： community structure complex network data mining community closeness

来源：评论

学校读者我要写书评

暂无评论

Interactive PBIL with Multiple Probability Vectors for Multimodal Optimization with Implicit Performance Indices

Interactive PBIL with Multiple Probability Vectors for Multi...

引用

2010 2nd International Conference on Computer Engineering and Technology(2010年第二届计算机工程与技术国际会议 ICCET 2010)

作者： Haifeng You Xufa Wang Department of Computer Science and Technology Anhui Key Laboratory of Software in Computing and Communication University of Science and Technology of China Hefei China

ISBN: (纸本)9781424463473

Interactive population-based incremental learning (IPBIL) is an effective method to solve optimization problems with implicit performance indices. It can significantly reduce user fatigue compared with interactive evolutionary computation (IEC). However,each run of IPBIL can only find one solution or some similar solutions. Thus it is not suitable for multimodal optimization problems with implicit performance indices. To solve this problem,we propose an IPBIL with multiple probability vectors (IPBIL-MPV) in this work. The key idea is to utilize multiple probability vectors to catch different search directions and thus find more than one solutions. We perform a subjective experiment in which IPBIL-MPV is applied to a fashion design problem. The experimental results show that IPBIL-MPV can find several distinct solutions in a run. Thus it is an effective method to solve multimodal optimization problems with implicit performance indices.

关键词： population-based incremental learning multimodal optimization:implicit performance indices:fashion design

来源：评论

学校读者我要写书评

暂无评论

A Hormone-based Clustering Algorithm in Wireless Sensor Networks

A Hormone-based Clustering Algorithm in Wireless Sensor Netw...

引用

2010 2nd International Conference on Computer Engineering and Technology(2010年第二届计算机工程与技术国际会议 ICCET 2010)

作者： Dayuan Dong Haifeng You Yipeng Zhang Xufa Wang Key Laboratory of Software in Computing and Communication Anhui Province School of Computer Science and Technology University of Science and Technology of China HefeiChina

ISBN: (纸本)9781424463473;9781424463497;9781424463503

Clustering problem is one of the hottest issues in wireless sensor networks (WSNs). The strategy for selection of cluster head has not been sufficiently investigated. In this paper,we propose a hormone-based clustering algorithm (HCA) inspired by the communication mechanism of bioendocrine system to prolong the lifetime of the sensor nodes. Two kinds of hormones,cluster hormone and member hormone,are used in the algorithm. Hormone message can promote a node to become a cluster head or a member node. Comparative experiment shows that the proposed algorithm has effectively prolong the lifetime of WSN compared with LEACH[1] and HEED[2].

关键词： hormone:clustering:wireless sensor networks

来源：评论

学校读者我要写书评

暂无评论

A preliminary study on why using the nonself detector set for anomaly detection in artificial immune Systems

A preliminary study on why using the nonself detector set fo...

引用

2009 International Conference on computational Intelligence and Security, CIS 2009

作者： Xu, Baoliang Luo, Wenjian Wang, Xufa Nature Inspired Computation and Applications Laboratory School of Computer Science and Technology University of Science and Technology of China Hefei 230027 Anhui China Anhui Key Laboratory of Software in Computing and Communication University of Science and Technology of China Hefei 230027 Anhui China

ISBN: (纸本)9780769539317

In artificial immune systems, the detectors in the nonself space are often adopted to detect anomaly changes, such as the negative selection algorithm and its improvements. Since the detectors in the self space can also be used to detect anomaly changes, a frequently asked question is which kind of detector sets is more efficient for a specific problem. In this paper, firstly, the advantages and disadvantages of the self detector set and the nonself detector set are briefly reviewed. Secondly, when the complete matching rule is adopted, the average time costs of employing the nonself detector set and the self detector set for anomaly detection are compared theoretically. Thirdly, simulated experiments are done, and experimental results demonstrate that the theoretical conclusion is essentially correct. © 2009 IEEE.

关键词： Immune system

来源：评论

学校读者我要写书评

暂无评论

Cooperative spectrum sensing with feedback

Cooperative spectrum sensing with feedback

引用

5th International Conference on Wireless communications, Networking and Mobile Computing, WiCOM 2009

作者： Ping, Zhu Jinglong, Li Xufa, Wang Anhui Province Key Laboratory of Software in Computing and Communication School of Computer Science and Technology University of Science and Technology of China Hefei Anhui China

ISBN: (纸本)9781424436934

One of the main objective of spectrum sensing is to detect spectrum opportunity quickly and accurately. Both of the two aspects can be improved by hardware upgrading and software optimization. In this paper, we concentrate on sensing accuracy, which, differs from previous solutions, will be enhanced by modification of network topology. We expand the traditional parallel fusion network (PFN) to parallel feedback fusion network (PFFN), in which local cognitive sensor makes its local decision based on previous global decision and its recent observation. We then derived optimal decision rules for PFFN. Moreover, based on PFFN, sensing history of local cognitive sensor is introduced and studied. Theoretical analysis and experimental results show that PFFN outperforms the PFN in smaller system error probability under the same SNR. We also proved that PFFN and PFFN with sensing history (PFFNSH) emphasize on different aspects when certain condition holds in real world applications. Finally, a general PFFN framework is proposed and discussed. ©2009 IEEE.

关键词： Feedback

来源：评论

学校读者我要写书评

暂无评论

Theoretical and empirical analyses of Evolutionary Negative Selection Algorithms for a combinational optimization problem

Theoretical and empirical analyses of Evolutionary Negative ...

引用

International Conference on Bio-Inspired Computing: Theories and Applications, BICTA

作者： Xingxin Pei Wenjian Luo Nature Inspired Computation and Application Laboratory School of Computer Science and Technology Anhui Key Laboratory of Software in Computing and Communication University of Science and Technology Hefei Anhui China

Evolutionary Negative Selection Algorithms (ENSAs) could be regarded as hybrid algorithms of Evolutionary Algorithms (EAs) and Negative Selection Algorithms (NSAs). The average time complexity of ENSAs on combinational optimization problems has never been studied before. In this paper, the average time complexity of ENSAs on one combinational optimization problem is analyzed. The theoretical results demonstrate that, for the Two Max function, the ENSA with an appropriate matching threshold could perform better than the traditional (N+N) EA. Some simulation experiments on the combinational problem are also done, and the experimental results are consistent with theoretical results.

关键词： Algorithm design and analysis software algorithms Immune system Convergence Laboratories Computer applications Application software Computer science Evolutionary computation Biology computing

来源：评论

学校读者我要写书评

暂无评论

Evolutionary Games on Weighted Newman-Watts Small-World Networks

引用

Chinese Physics Letters 2009年第5期26卷 255-258页

作者：杜文博曹先彬赵琳周宏 Department of Computer Science and Technology University of Science and Technology of China Hefei 230026 Anhui Province Key Laboratory of Software in Computing and Communication University of Science and Technology of China Hefei 230026 School of Life Sciences University of Science and Technology of China Hefei 230026

We investigate the evolutionary prisoner＇s dilemma game （PDG） on weighted Newman-Watts （NW） networks. In weighted NW networks, the link weight ωij is assigned to the link between the nodes i and j as： ωij = （ki · kj）^β, where ki（kj） is the degree of node i（j） and β represents the strength of the correlations. Obviously, the link weight can be tuned by only one parameter β. We focus on the cooperative behavior and wealth distribution in the system. Simulation results show that the cooperator frequency is promoted by a large range of β and there is a minimal cooperation frequency around β = -1. Moreover, we also employ the Gini coefficient to study the wealth distribution in the population. Numerical results show that the Gini coefficient reaches its minimum when β≈ -1. Our work may be helpful in understanding the emergence of cooperation and unequal wealth distribution in society.

关键词： PRISONER'S dilemma game COOPERATIVENESS INCOME distribution SIMULATION methods & models GINI coefficient NUMERICAL analysis

来源：评论

学校读者我要写书评

暂无评论

A Preliminary Study on Why Using the Nonself Detector Set for Anomaly Detection in Artificial Immune Systems

A Preliminary Study on Why Using the Nonself Detector Set fo...

引用

International Conference on computational Intelligence and Security

作者： Baoliang Xu Wenjian Luo Xufa Wang Anhui Key Laboratory of Software in Computing and Communication University of Science and Technology Hefei Anhui China University of Science and Technology of China Hefei Anhui CN

ISBN: (纸本)9781424454112

关键词： Detectors Artificial immune systems Space technology Costs Immune system Biological system modeling Monitoring Laboratories Intrusion detection Biology computing

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：