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Iris verification based on fractional Fourier transform 基于分数阶傅里叶变换的虹膜验证
Proceedings. International Conference on Machine Learning and Cybernetics Pub Date : 2002-11-04 DOI: 10.1109/ICMLC.2002.1167451
Li Yu, Kuanquan Wang, Chengfa Wang, D. Zhang
{"title":"Iris verification based on fractional Fourier transform","authors":"Li Yu, Kuanquan Wang, Chengfa Wang, D. Zhang","doi":"10.1109/ICMLC.2002.1167451","DOIUrl":"https://doi.org/10.1109/ICMLC.2002.1167451","url":null,"abstract":"Iris verification is one of the biometrics verification technologies. This paper proposes a new iris verification method based on fractional Fourier transform. Through comparing two irises' fractional Fourier transform, we can distinguish the people whether they are the same person. At last, we introduce some applications of iris verification used for security in e-commerce.","PeriodicalId":90702,"journal":{"name":"Proceedings. International Conference on Machine Learning and Cybernetics","volume":"47 1","pages":"1470-1473 vol.3"},"PeriodicalIF":0.0,"publicationDate":"2002-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84568881","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: 23
A social cognition model applied to general combinatorial optimization problem 应用于一般组合优化问题的社会认知模型
Proceedings. International Conference on Machine Learning and Cybernetics Pub Date : 2002-11-04 DOI: 10.1109/ICMLC.2002.1167392
Yixin Yu, Hong-Peng Mang
{"title":"A social cognition model applied to general combinatorial optimization problem","authors":"Yixin Yu, Hong-Peng Mang","doi":"10.1109/ICMLC.2002.1167392","DOIUrl":"https://doi.org/10.1109/ICMLC.2002.1167392","url":null,"abstract":"A brief introduction to a social cognition study and perspectives of its application to engineering problems are given. Since many complicated combinatorial optimization problems still lack effective solution methods, a general comprehension of a combinatorial optimization problem and a mathematical model for it are mainly discussed. Through imitating some phenomena of the organization and evolution of human society, a social cognition model is proposed. This model has superior applicability to most kinds of combinatorial optimization problems. It has been shown that this model has higher computation efficiency and higher convergence stability than traditional genetic algorithms through a power distribution network planning example.","PeriodicalId":90702,"journal":{"name":"Proceedings. International Conference on Machine Learning and Cybernetics","volume":"42 1","pages":"1208-1213 vol.3"},"PeriodicalIF":0.0,"publicationDate":"2002-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84982040","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: 4
Evolving support vector machine parameters 进化支持向量机参数
Proceedings. International Conference on Machine Learning and Cybernetics Pub Date : 2002-11-04 DOI: 10.1109/ICMLC.2002.1176817
Anh Trần Quang, Qianli Zhang, Xing Li
{"title":"Evolving support vector machine parameters","authors":"Anh Trần Quang, Qianli Zhang, Xing Li","doi":"10.1109/ICMLC.2002.1176817","DOIUrl":"https://doi.org/10.1109/ICMLC.2002.1176817","url":null,"abstract":"The kernel type, kernel parameters and upper bound C control the generalization of support vector machines. The best choice of kernel or C depends on each other and the art of researchers. This paper presents a general optimization problem of support vector machine parameters including a mixed kernel and different upper bounds for unbalanced data. The objectives are /spl xi/a-estimators of the error rate, recall and precision. Evolutionary algorithms are used to solve the problem. The performance of this method is illustrated with a standard data set of intrusion detection application.","PeriodicalId":90702,"journal":{"name":"Proceedings. International Conference on Machine Learning and Cybernetics","volume":"57 1","pages":"548-551 vol.1"},"PeriodicalIF":0.0,"publicationDate":"2002-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85116442","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: 34
Study on discretization based on rough set theory 基于粗糙集理论的离散化研究
Proceedings. International Conference on Machine Learning and Cybernetics Pub Date : 2002-11-04 DOI: 10.1109/ICMLC.2002.1167430
Jian-hua Dai, Yuan-xiang Li
{"title":"Study on discretization based on rough set theory","authors":"Jian-hua Dai, Yuan-xiang Li","doi":"10.1109/ICMLC.2002.1167430","DOIUrl":"https://doi.org/10.1109/ICMLC.2002.1167430","url":null,"abstract":"Discretization of attributes with real values is an important problem in data mining based on rough set. And discretization based on rough set has some particular characteristics. The method of discretization based on rough set and Boolean reasoning is discussed. Determination of. candidate cuts is discussed in detail. A theorem is proposed. to show that all bound cuts can discern the same objects pairs as the whole initial cuts. A strategy to select candidate cuts is proposed based on the theorem. Under the strategy, the space complexity and time complexity of improved algorithm decline obviously. The experiments results also confirm that.","PeriodicalId":90702,"journal":{"name":"Proceedings. International Conference on Machine Learning and Cybernetics","volume":"8 1","pages":"1371-1373 vol.3"},"PeriodicalIF":0.0,"publicationDate":"2002-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85132191","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: 31
Multi-scale reinforcement learning with fuzzy state 模糊状态下的多尺度强化学习
Proceedings. International Conference on Machine Learning and Cybernetics Pub Date : 2002-11-04 DOI: 10.1109/ICMLC.2002.1167464
X. Zhuang, Qing-chun Meng, Han-Ping Wang, B. Yin
{"title":"Multi-scale reinforcement learning with fuzzy state","authors":"X. Zhuang, Qing-chun Meng, Han-Ping Wang, B. Yin","doi":"10.1109/ICMLC.2002.1167464","DOIUrl":"https://doi.org/10.1109/ICMLC.2002.1167464","url":null,"abstract":"In this paper, multi-scale reinforcement learning is presented based on fuzzy state. The concept of fuzzy state is proposed to enable multi-scale representation of the state space. The performance of different learning scales is investigated, based on which a multi-scale learning approach is proposed to increase the learning speed while keeping the learning accuracy. The multi-scale learning approach is applied to the robot navigation problem in the computer simulation experiment. In a multi-obstacle environment, the multi-scale reinforcement learning approach shows better performance than the traditional reinforcement learning method.","PeriodicalId":90702,"journal":{"name":"Proceedings. International Conference on Machine Learning and Cybernetics","volume":"57 1","pages":"1523-1528 vol.3"},"PeriodicalIF":0.0,"publicationDate":"2002-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85671773","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: 0
Neural network credit-risk evaluation model based on back-propagation algorithm 基于反向传播算法的神经网络信用风险评估模型
Proceedings. International Conference on Machine Learning and Cybernetics Pub Date : 2002-11-04 DOI: 10.1109/ICMLC.2002.1175325
Rongzhou Li, Sulin Pang, Jian-min Xu
{"title":"Neural network credit-risk evaluation model based on back-propagation algorithm","authors":"Rongzhou Li, Sulin Pang, Jian-min Xu","doi":"10.1109/ICMLC.2002.1175325","DOIUrl":"https://doi.org/10.1109/ICMLC.2002.1175325","url":null,"abstract":"The research establishes a neural network credit-risk evaluation model by using back-propagation algorithm. The model is evaluated by the credits for 120 applicants. The 120 data are separated in three groups: a \"good credit\" group, a \"middle credit\" group and a \"bad credit\" group. The simulation shows that the neural network credit-risk evaluation model has higher classification accuracy compared with the traditional parameter statistical approach, that is linear discriminant analysis. We still give a learning algorithm and a corresponding algorithm of the model.","PeriodicalId":90702,"journal":{"name":"Proceedings. International Conference on Machine Learning and Cybernetics","volume":"39 1","pages":"1702-1706 vol.4"},"PeriodicalIF":0.0,"publicationDate":"2002-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85924180","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: 23
Research and development in Web usage mining system-key issues and proposed solutions: a survey Web使用挖掘系统研究与开发中的关键问题及解决方案综述
Proceedings. International Conference on Machine Learning and Cybernetics Pub Date : 2002-11-04 DOI: 10.1109/ICMLC.2002.1174531
Feng Zhang, Huiyou Chang
{"title":"Research and development in Web usage mining system-key issues and proposed solutions: a survey","authors":"Feng Zhang, Huiyou Chang","doi":"10.1109/ICMLC.2002.1174531","DOIUrl":"https://doi.org/10.1109/ICMLC.2002.1174531","url":null,"abstract":"Web mining can be classified into three domains: Web structure mining, Web content mining and Web usage mining. There are generally three tasks in Web usage mining: preprocessing, knowledge discovery and pattern analysis. Though Web usage mining is still ranged in the application of traditional data mining techniques, in view of changes in application environment and data concerned, some new difficulties have arisen accordingly. The paper takes efforts to address such challenges in the three phases and introduces some proposed solutions simultaneously.","PeriodicalId":90702,"journal":{"name":"Proceedings. International Conference on Machine Learning and Cybernetics","volume":"63 1","pages":"986-990 vol.2"},"PeriodicalIF":0.0,"publicationDate":"2002-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80922771","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: 33
Model-free control based on neural networks 基于神经网络的无模型控制
Proceedings. International Conference on Machine Learning and Cybernetics Pub Date : 2002-11-04 DOI: 10.1109/ICMLC.2002.1175425
Zhongjiu Zheng, Ning Wang
{"title":"Model-free control based on neural networks","authors":"Zhongjiu Zheng, Ning Wang","doi":"10.1109/ICMLC.2002.1175425","DOIUrl":"https://doi.org/10.1109/ICMLC.2002.1175425","url":null,"abstract":"A model-free control method for nonlinear plants is proposed. According to the neuron model and learning strategy in Wang et al. (1991), the neural network model is structured and the learning algorithm is also presented. Based on the neural network, the model-free controller is designed. In an example of control of a pH process, the simulation results show that the proposed control method can control a nonlinear plant efficiently.","PeriodicalId":90702,"journal":{"name":"Proceedings. International Conference on Machine Learning and Cybernetics","volume":"35 1","pages":"2180-2183 vol.4"},"PeriodicalIF":0.0,"publicationDate":"2002-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85554746","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
Relative term-frequency based feature selection for text categorization 基于相对词频的文本分类特征选择
Proceedings. International Conference on Machine Learning and Cybernetics Pub Date : 2002-11-04 DOI: 10.1109/ICMLC.2002.1167443
S.M. Yang, Xiaogang Wu, Zhihong Deng, Ming Zhang, Dongqing Yang
{"title":"Relative term-frequency based feature selection for text categorization","authors":"S.M. Yang, Xiaogang Wu, Zhihong Deng, Ming Zhang, Dongqing Yang","doi":"10.1109/ICMLC.2002.1167443","DOIUrl":"https://doi.org/10.1109/ICMLC.2002.1167443","url":null,"abstract":"Automatic feature selection methods such as document frequency, information gain, mutual information and so on are commonly applied in the preprocess of text categorization in order to reduce the originally high feature dimension to a bearable level, meanwhile also reduce the noise to improve precision. Generally they assess a specific term by calculating its occurrences among individual categories or in the entire corpus, where \"occurring in a document\" is simply defined as occurring at least once. A major drawback of this measure is that, for a single document, it might count a recurrent term the same as a rare term, while the former term is obviously more informative and should less likely be removed. In this paper we propose a possible approach to overcome this problem, which adjusts the occurrences count according to the relative term frequency, thus stressing those recurrent words in each document. While it can be applied to all feature selection methods, we implemented it on several of them and see notable improvements in the performances.","PeriodicalId":90702,"journal":{"name":"Proceedings. International Conference on Machine Learning and Cybernetics","volume":"1 1","pages":"1432-1436 vol.3"},"PeriodicalIF":0.0,"publicationDate":"2002-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77841650","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: 24
Meta-information in rough set theory 粗糙集理论中的元信息
Proceedings. International Conference on Machine Learning and Cybernetics Pub Date : 2002-11-04 DOI: 10.1109/ICMLC.2002.1174471
Jian Su, Ji Gao
{"title":"Meta-information in rough set theory","authors":"Jian Su, Ji Gao","doi":"10.1109/ICMLC.2002.1174471","DOIUrl":"https://doi.org/10.1109/ICMLC.2002.1174471","url":null,"abstract":"In original rough set theory, an information system is represented as a single data table describing a set of objects by a set of attributes. In this paper, the information system is generalized by considering a family of subsystems. An information system with more than one subsystem is called a distributed information system. A new concept called meta-information is presented to describe an information system or its subsystems. Algorithms for meta-information integration and derived meta-information generation are proposed. Many existing methods can be reimplemented on the basis of meta-information to avoid the costly work of data integration. Operations on meta-information are very simple and cost-effective. Some applications of meta-information are also discussed.","PeriodicalId":90702,"journal":{"name":"Proceedings. International Conference on Machine Learning and Cybernetics","volume":"32 1","pages":"729-734 vol.2"},"PeriodicalIF":0.0,"publicationDate":"2002-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76654657","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: 2
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