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2007 IEEE International Conference on Granular Computing (GRC 2007)最新文献

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New Computational Model from Ant Colony 蚁群的新计算模型
2007 IEEE International Conference on Granular Computing (GRC 2007) Pub Date : 2007-11-02 DOI: 10.1109/GrC.2007.26
Wei Gao
{"title":"New Computational Model from Ant Colony","authors":"Wei Gao","doi":"10.1109/GrC.2007.26","DOIUrl":"https://doi.org/10.1109/GrC.2007.26","url":null,"abstract":"The computational model from life system has become a main intelligent algorithm. Ant colony algorithm is a new computational model from mimic the swarm intelligence of ant colony behavior. And it is a very good combination optimization method. To extend the ant colony algorithm, some continuous ant colony algorithms have been proposed. To improve the searching performance, the principles of evolutionary algorithm and immune system have been combined with the typical continuous ant colony algorithm, and one new computational model is proposed here. In this new model, the ant individual is transformed by adaptive Cauchi mutation and thickness selection. To verify the new computational model, the typical functions, such as Schaffer function is used. And then, the results of new algorithm are compared with that of ant colony algorithm and immunized evolutionary programming which is proposed by author. The results show that, the convergent speed and computing precision of new algorithm are all very good.","PeriodicalId":259430,"journal":{"name":"2007 IEEE International Conference on Granular Computing (GRC 2007)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133145486","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 14
The Worse Clustering Performance Analysis 较差聚类性能分析
2007 IEEE International Conference on Granular Computing (GRC 2007) Pub Date : 2007-11-02 DOI: 10.1109/GrC.2007.74
Jian Yu, Pengwei Hao
{"title":"The Worse Clustering Performance Analysis","authors":"Jian Yu, Pengwei Hao","doi":"10.1109/GrC.2007.74","DOIUrl":"https://doi.org/10.1109/GrC.2007.74","url":null,"abstract":"Partitional clustering algorithms are the most widely used in pattern recognition fields. And the output of partitional clustering is sensitive to the initial parameters. Therefore, it is very important to choose the optimal parameter for a specific clustering algorithm. In the past, parameter selection usually is up to the empirically optimal clustering performance. In this paper, we propose a novel approach to parameter selection for partitional clustering based on the stability analysis of dynamical system. The main idea is as follows: any clustering algorithm can not always partition a data set into meaningful subsets, therefore the parameters corresponding to the worse clustering result should not be the optimal, especially for those corresponding to the stable worse clustering output. Such framework is called the worse clustering performance analysis. As its application, we not only present how to do parameter selection for several clustering models, but also reveal that the extreme point of its objective function does not guarantee to be the stable fixed point of this clustering algorithm. From a machine learning point of view, such conclusion means that the learning algorithm maybe not reach its original expectation under some circumstance.","PeriodicalId":259430,"journal":{"name":"2007 IEEE International Conference on Granular Computing (GRC 2007)","volume":"345 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115892198","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Meaning of Pearson Residuals Linear Algebra View 线性代数中Pearson残差的意义
2007 IEEE International Conference on Granular Computing (GRC 2007) Pub Date : 2007-11-02 DOI: 10.1109/GrC.2007.126
S. Tsumoto, S. Hirano
{"title":"Meaning of Pearson Residuals Linear Algebra View","authors":"S. Tsumoto, S. Hirano","doi":"10.1109/GrC.2007.126","DOIUrl":"https://doi.org/10.1109/GrC.2007.126","url":null,"abstract":"Marginal distributions play an central role in statistical analysis of a contingency table. However, when the number of partition becomes large, the contribution from marginal distributions decreases. This paper focuses on a formal analysis of marginal distributions in a contingency table. The main approach is to take the difference between two matrices with the same sample size and the same marginal distributions, which we call difference matrix. The important nature of the difference matrix is that the determinant is equal to 0: when the rank of a matrix is r, the difference between a original matrix and the expected matrix will become r - 1 at most. Since the sum of rows or columns of the will become zero, which means that the information of one rank corresponds to information on the frequency of a contingency matrix. Interestingly, if we take an expected matrix whose elements are the expected values based on marginal distributions, the difference between an original matrix and expected matrix can be represented by linear combination of determinants of 2 times 2 submatrices.","PeriodicalId":259430,"journal":{"name":"2007 IEEE International Conference on Granular Computing (GRC 2007)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122005448","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 3
Agglomerative Hierarchical Clustering for Data with Tolerance 具有容错数据的聚类层次聚类
2007 IEEE International Conference on Granular Computing (GRC 2007) Pub Date : 2007-11-02 DOI: 10.1109/GrC.2007.107
Y. Endo, Y. Hamasuna, S. Miyamoto
{"title":"Agglomerative Hierarchical Clustering for Data with Tolerance","authors":"Y. Endo, Y. Hamasuna, S. Miyamoto","doi":"10.1109/GrC.2007.107","DOIUrl":"https://doi.org/10.1109/GrC.2007.107","url":null,"abstract":"This paper presents new clustering algorithms which are based on agglomerative hierarchical clustering (AHC) with centroid method. The algorithms can handle with data with tolerance of which the concept includes some errors, ranges, or missing values in data. First, the tolerance is introduced into optimization problems of clustering. Second, an objective function is introduced for calculating the centroid of cluster and the problem is solved using Kuhn-Tucker conditions. Next, new algorithms are constructed based on the solution of the problem. Finally, the effectiveness of the proposed algorithms in this paper is verified through some numeric examples for the artificial data.","PeriodicalId":259430,"journal":{"name":"2007 IEEE International Conference on Granular Computing (GRC 2007)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129772962","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
MHC Regulation Based Immune Formula Discovering Algorithm (IFDA) 基于MHC调控的免疫公式发现算法
2007 IEEE International Conference on Granular Computing (GRC 2007) Pub Date : 2007-11-02 DOI: 10.1109/GrC.2007.28
Min Hu, Weiming Sun
{"title":"MHC Regulation Based Immune Formula Discovering Algorithm (IFDA)","authors":"Min Hu, Weiming Sun","doi":"10.1109/GrC.2007.28","DOIUrl":"https://doi.org/10.1109/GrC.2007.28","url":null,"abstract":"After having analyzed the advantage and disadvantage of gene expression programming (GEP), this paper proposes an innovative immune formula discovering algorithm (IFDA), which is actually inspired by MHC (major histocompatibility complex) regulation principle of immune theory. In IFDA, the formula are mapped as tree structure and transformed into both constant and variation section of antibody with a depth- first mechanism while its fragment is encoded into the MHC. Using the feature of MHC regulation, IFDA provides a quick solution to discover the proper formula. Many benchmark data are used for verifying the performance of IFDA in which all results from experiments show that the IFDA can really provide better performance than GEP.","PeriodicalId":259430,"journal":{"name":"2007 IEEE International Conference on Granular Computing (GRC 2007)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128415619","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 15
An Application of CP Neural Network Based on Rough Set in Image Edge Detection 基于粗糙集的CP神经网络在图像边缘检测中的应用
2007 IEEE International Conference on Granular Computing (GRC 2007) Pub Date : 2007-11-02 DOI: 10.1109/GrC.2007.23
Min Dong, HuiYu Jiang, Xiangpeng Li, Qing Liu
{"title":"An Application of CP Neural Network Based on Rough Set in Image Edge Detection","authors":"Min Dong, HuiYu Jiang, Xiangpeng Li, Qing Liu","doi":"10.1109/GrC.2007.23","DOIUrl":"https://doi.org/10.1109/GrC.2007.23","url":null,"abstract":"Based on the rough set theory, a counter propagation neural network algorithm for edge detection is presented in this paper. Firstly, a definition of rough membership function, which is used to modify the weigh values in the nomal counter propagation neural network, is proposed after introducing the rough set. Experiments show that the approach has achieved good results in improving the accuracy of detection. And this algorithm can also overcome effectively the problem of simply cluster in the nomal counter propagation neural network.","PeriodicalId":259430,"journal":{"name":"2007 IEEE International Conference on Granular Computing (GRC 2007)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122318548","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 8
A Study of Bioelectrical Impedance Analysis Methods for Practical Visceral Fat Estimation 实用内脏脂肪估计的生物电阻抗分析方法研究
2007 IEEE International Conference on Granular Computing (GRC 2007) Pub Date : 2007-11-02 DOI: 10.1109/GrC.2007.109
M. Yoneda, Hiroshi Tasaki, N. Tsuchiya, H. Nakajima, Takehiro Hamaguchi, Shojiro Oku, T. Shiga
{"title":"A Study of Bioelectrical Impedance Analysis Methods for Practical Visceral Fat Estimation","authors":"M. Yoneda, Hiroshi Tasaki, N. Tsuchiya, H. Nakajima, Takehiro Hamaguchi, Shojiro Oku, T. Shiga","doi":"10.1109/GrC.2007.109","DOIUrl":"https://doi.org/10.1109/GrC.2007.109","url":null,"abstract":"The method of bioelectrical impedance-based visceral fat estimation is in advance of other methods such as X-ray CT or MRI from the point views of cost and safety. However, it requires complex and diversity signal analysis and modeling to realize its high estimation accuracy. In response to this requirement, complication of feature attributes and simplification in selection of them to model the estimation has been proposed and evaluated in this paper. The complication of feature attributes is realized by applying priori knowledge and by employing the idea of cardinality as quantitative evaluation index. The simplification of the estimation model is realized by employing Akaike information criteria. The experiments were conducted to evaluate the proposed method and the results prove high estimation accuracy and stability of the proposed method.","PeriodicalId":259430,"journal":{"name":"2007 IEEE International Conference on Granular Computing (GRC 2007)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116267080","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 30
Design and Implementation of Intranet Security Audit System Based on Load Balancing 基于负载均衡的内网安全审计系统的设计与实现
2007 IEEE International Conference on Granular Computing (GRC 2007) Pub Date : 2007-11-02 DOI: 10.1109/GrC.2007.64
Baixing Chen, Xiufen Fu, Xiayu Zhang, Lei Su, Dan Wu
{"title":"Design and Implementation of Intranet Security Audit System Based on Load Balancing","authors":"Baixing Chen, Xiufen Fu, Xiayu Zhang, Lei Su, Dan Wu","doi":"10.1109/GrC.2007.64","DOIUrl":"https://doi.org/10.1109/GrC.2007.64","url":null,"abstract":"Intranet security is the hotspot of network security researching field nowadays. This paper discusses the load balancing based on the research and analysis of present intranet security audit systems. It puts forward a system structure and model of the Intranet security audit systems based on load balancing. The model gathers dynamic load balancing of the cluster servers in security audit to effectively solve the bottleneck problem of the distributed audit system which has control centre. Finally, it describes the design and the implementation of the key system module.","PeriodicalId":259430,"journal":{"name":"2007 IEEE International Conference on Granular Computing (GRC 2007)","volume":"294 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132579435","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 7
Study on the Axis Problem of Rough 3-Valued Algebras 粗糙3值代数的轴问题研究
2007 IEEE International Conference on Granular Computing (GRC 2007) Pub Date : 2007-11-02 DOI: 10.1109/GrC.2007.61
Jianhua Dai
{"title":"Study on the Axis Problem of Rough 3-Valued Algebras","authors":"Jianhua Dai","doi":"10.1109/GrC.2007.61","DOIUrl":"https://doi.org/10.1109/GrC.2007.61","url":null,"abstract":"The collection of all the rough sets of an approximation space can be made into a 3-valued Lukasiewicz algebra. Thus, we call the algebra constructed by the collection of rough sets of an approximation space a rough 3-valued Lukasiewicz algebra. In this paper, whether the rough 3-valued Lukasiewicz algebra is an axled 3-valued Lukasiewicz algebra is examined.","PeriodicalId":259430,"journal":{"name":"2007 IEEE International Conference on Granular Computing (GRC 2007)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131997291","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 5
Intelligent Search Engine Based on Formal Concept Analysis 基于形式概念分析的智能搜索引擎
2007 IEEE International Conference on Granular Computing (GRC 2007) Pub Date : 2007-11-02 DOI: 10.1109/GrC.2007.62
Xiajiong Shen, Yan Xu, Junyang Yu, Ke Zhang
{"title":"Intelligent Search Engine Based on Formal Concept Analysis","authors":"Xiajiong Shen, Yan Xu, Junyang Yu, Ke Zhang","doi":"10.1109/GrC.2007.62","DOIUrl":"https://doi.org/10.1109/GrC.2007.62","url":null,"abstract":"Due to most query technique in Chinese information retrieval is based on keyword matching, existing Search Engines return excessive information. So there are those directions that future search engines are pursuing to, such as how to express the information requirement, how to lay out and browse the information structure, and how to build individuated and intelligent model based on information requirement etc. Therefore, intelligent search engine based on conceptual relations is the best way to answer for the need of information retrieval. In this paper we put forward an intelligent search engine which Information Retrieval model is found on formal context of FCA (formal concept analysis) and incorporates with a browsing mechanism for such a system based on the concept lattice. Test data validates its feasibility, and implement of the FCA-search engine indicates that the concept lattice of FCA is a useful way of supporting the flexible management of documents according to conceptual relation.","PeriodicalId":259430,"journal":{"name":"2007 IEEE International Conference on Granular Computing (GRC 2007)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114164352","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 15
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