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Proceedings. International Conference on Machine Learning and Cybernetics最新文献

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A study on gray neural network modeling 灰色神经网络建模研究
Proceedings. International Conference on Machine Learning and Cybernetics Pub Date : 2002-11-04 DOI: 10.1109/ICMLC.2002.1175391
L. Zhong, Jingling Yuan, Hongxia Xia, Chengming Zou
{"title":"A study on gray neural network modeling","authors":"L. Zhong, Jingling Yuan, Hongxia Xia, Chengming Zou","doi":"10.1109/ICMLC.2002.1175391","DOIUrl":"https://doi.org/10.1109/ICMLC.2002.1175391","url":null,"abstract":"In order to resolve complex gray uncertainly problems, the gray neural network modeling (GNNM) method by combining gray system theory with neural network is studied and improved in the paper. Also, a method of GNNM (1, 1) based on the time response model is proposed. With an eye to the multidimensional indefinite problems in which all kinds of genetic relationships and mechanisms exist, GNNM (1, 4) is established on the basis of GNNM (1, 1).","PeriodicalId":90702,"journal":{"name":"Proceedings. International Conference on Machine Learning and Cybernetics","volume":"55 1","pages":"2021-2023 vol.4"},"PeriodicalIF":0.0,"publicationDate":"2002-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84835802","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: 13
The study of epistasis based on the random walk model in fitness landscapes of schemata 基于随机游走模型的模式适应度景观上位性研究
Proceedings. International Conference on Machine Learning and Cybernetics Pub Date : 2002-11-04 DOI: 10.1109/ICMLC.2002.1167435
Jian-Wu Li, Min-Qiang Li
{"title":"The study of epistasis based on the random walk model in fitness landscapes of schemata","authors":"Jian-Wu Li, Min-Qiang Li","doi":"10.1109/ICMLC.2002.1167435","DOIUrl":"https://doi.org/10.1109/ICMLC.2002.1167435","url":null,"abstract":"Interdependence between genes is an important factor causing hardness in genetic algorithms (GA). Traditional methods, which are used to measure the interaction between genes, can only reflect the extent of epistasis between all genes in the chromosome. In this paper, we propose the definition of the fitness landscape of schemata, and perform random walks on this landscape to study the degree of interdependence between some certain gene loci in study. According to the degree of interaction between these given gene loci, we can analyze and determine building blocks of GA. We also do a lot of experiments based on NK-models, and results of empirical analysis show that this method is effective.","PeriodicalId":90702,"journal":{"name":"Proceedings. International Conference on Machine Learning and Cybernetics","volume":"107 1","pages":"1396-1400 vol.3"},"PeriodicalIF":0.0,"publicationDate":"2002-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77595437","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
Matrix criterion for dynamic analysis in discrete neural networks with multiple delays 多时滞离散神经网络动态分析的矩阵准则
Proceedings. International Conference on Machine Learning and Cybernetics Pub Date : 2002-11-04 DOI: 10.1109/ICMLC.2002.1175439
Eric C. C. Tsang, S. Qiu, D. Yeung
{"title":"Matrix criterion for dynamic analysis in discrete neural networks with multiple delays","authors":"Eric C. C. Tsang, S. Qiu, D. Yeung","doi":"10.1109/ICMLC.2002.1175439","DOIUrl":"https://doi.org/10.1109/ICMLC.2002.1175439","url":null,"abstract":"The dynamics of a discrete Hopfield neural network with multiple delays (HNNMDs) is studied by using a matrix inequality which is shown to be equivalent to the state transition equation of the HNNMDs network. Earlier work (2000) on discrete Hopfield neural networks showed that a parallel or serial mode of operation always leads to a limit cycle of period one or two for a skew or symmetric matrix, but they did not give an arbitrary weight matrix on how an updating operation might be needed to reach such a cycle. In this paper we present the existence conditions of limit cycles using matrix criteria in the HNNMDs network. For a network with an arbitrary weight matrix, the necessary and sufficient conditions for the existence of a limit cycle of period 1 and r are provided. The conditions for the existence of a special limit cycle of period 1 and 2 are also found. These results provide the foundation for many applications. A HNNMDs is said to have no stable state (fixed point) if it has a limit cycle of period 2 or more, which is stated in Theorem 5. A computer simulation demonstrates that the theoretical analysis in Theorem 5 is correct.","PeriodicalId":90702,"journal":{"name":"Proceedings. International Conference on Machine Learning and Cybernetics","volume":"44 1","pages":"2245-2250 vol.4"},"PeriodicalIF":0.0,"publicationDate":"2002-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86906667","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
Correlation based generating rules for fuzzy classification 基于关联的模糊分类生成规则
Proceedings. International Conference on Machine Learning and Cybernetics Pub Date : 2002-11-04 DOI: 10.1109/ICMLC.2002.1175333
Da-Zhong Liu, Xizhao Wang, J.W.T. Lee
{"title":"Correlation based generating rules for fuzzy classification","authors":"Da-Zhong Liu, Xizhao Wang, J.W.T. Lee","doi":"10.1109/ICMLC.2002.1175333","DOIUrl":"https://doi.org/10.1109/ICMLC.2002.1175333","url":null,"abstract":"Automated acquisition of rules is a very important issue in knowledge engineering. In this paper, a new method for generating fuzzy rules from numerical data for fuzzy classification problems based on the correlation analysis between two fuzzy sets has been proposed. Experimental results and comparison with Yuan and Shaw's method are presented as well.","PeriodicalId":90702,"journal":{"name":"Proceedings. International Conference on Machine Learning and Cybernetics","volume":"5 1","pages":"1733-1736 vol.4"},"PeriodicalIF":0.0,"publicationDate":"2002-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87752930","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
Feature selection in recognition of handwritten Chinese characters 手写体汉字识别中的特征选择
Proceedings. International Conference on Machine Learning and Cybernetics Pub Date : 2002-11-04 DOI: 10.1109/ICMLC.2002.1167382
Li-xin Zhang, Yannan Zhao, Zehong Yang, Jiaxin Wang
{"title":"Feature selection in recognition of handwritten Chinese characters","authors":"Li-xin Zhang, Yannan Zhao, Zehong Yang, Jiaxin Wang","doi":"10.1109/ICMLC.2002.1167382","DOIUrl":"https://doi.org/10.1109/ICMLC.2002.1167382","url":null,"abstract":"Recognition of handwritten Chinese characters is a large-scale pattern recognition task, which is difficult and time consuming to build the corresponding classifiers. In this paper, two feature selection methods are proposed to reduce the complexity and speed up the handwritten Chinese recognition: one is the ReliefF-Wrapper method which evaluates the original features with the ReliefF method, and then uses the wrapper method to decide the number of features to be selected; and the other is GA-Wrapper that uses genetic algorithm to search the optimal subset of features with high training accuracy. Experiments were performed on 800 most frequently used Chinese characters, with 80,000 handwritten samples. Results show that the ReliefF-Wrapper method has good interpretation and high speed and GA-Wrapper gains higher accuracy. Limitations of the both methods and future work are also discussed.","PeriodicalId":90702,"journal":{"name":"Proceedings. International Conference on Machine Learning and Cybernetics","volume":"20 1","pages":"1158-1162 vol.3"},"PeriodicalIF":0.0,"publicationDate":"2002-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90362531","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: 9
Use of immune self-adaptation wavelet for data mining 免疫自适应小波在数据挖掘中的应用
Proceedings. International Conference on Machine Learning and Cybernetics Pub Date : 2002-11-04 DOI: 10.1109/ICMLC.2002.1176729
Jianguo Zheng, Ping Song
{"title":"Use of immune self-adaptation wavelet for data mining","authors":"Jianguo Zheng, Ping Song","doi":"10.1109/ICMLC.2002.1176729","DOIUrl":"https://doi.org/10.1109/ICMLC.2002.1176729","url":null,"abstract":"Based on an existing artificial neural network, a learning algorithm of the immune self-adaptation wavelet neural network is proposed which integrates the immune mechanism and the structure of neural information processing. This model makes it easy for a user to directly utilize the characteristic information of a pending problem and to simplify the original structure through adjusting the activation function with prior knowledge. Theoretical analysis and a simulation test for a data mining problem show that this method is effective and feasible.","PeriodicalId":90702,"journal":{"name":"Proceedings. International Conference on Machine Learning and Cybernetics","volume":"33 1","pages":"156-160 vol.1"},"PeriodicalIF":0.0,"publicationDate":"2002-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74055273","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
Research on Chinese character recognition post-processing based on genetic algorithm 基于遗传算法的汉字识别后处理研究
Proceedings. International Conference on Machine Learning and Cybernetics Pub Date : 2002-11-04 DOI: 10.1109/ICMLC.2002.1175329
Ke-jian Wang, Xue-dong Tian, Bao-lan Guo
{"title":"Research on Chinese character recognition post-processing based on genetic algorithm","authors":"Ke-jian Wang, Xue-dong Tian, Bao-lan Guo","doi":"10.1109/ICMLC.2002.1175329","DOIUrl":"https://doi.org/10.1109/ICMLC.2002.1175329","url":null,"abstract":"In order to improve the accuracy of a character recognition system, especially to improve recognition rate, it is positively significant to introduce an excellent post-processing method. A Chinese character recognition post-processing (CCRP) based on genetic algorithm is introduced in this paper. The genetic algorithm relies on the Chinese character itself and context information. Experiment shows that this method obtains quite good result. The character recognition rate of the tested text is from 94.99% to 95.92% after post-processing and improves 0.93%.","PeriodicalId":90702,"journal":{"name":"Proceedings. International Conference on Machine Learning and Cybernetics","volume":"21 1","pages":"1718-1721 vol.4"},"PeriodicalIF":0.0,"publicationDate":"2002-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73632388","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
Construction and application of Bayesian networks in flood decision supporting system 贝叶斯网络在洪水决策支持系统中的构建与应用
Proceedings. International Conference on Machine Learning and Cybernetics Pub Date : 2002-11-04 DOI: 10.1109/ICMLC.2002.1174468
Shaozhong Zhang, Nan-Hai Yang, Xiu-kun Wang
{"title":"Construction and application of Bayesian networks in flood decision supporting system","authors":"Shaozhong Zhang, Nan-Hai Yang, Xiu-kun Wang","doi":"10.1109/ICMLC.2002.1174468","DOIUrl":"https://doi.org/10.1109/ICMLC.2002.1174468","url":null,"abstract":"A Bayesian network is a graphical model that encodes probabilistic relationships among variables of interest. Bayesian networks are based on probability theory. We describe the principle of Bayesian probability and Bayesian networks. The automated creation of Bayesian networks can be separated into two tasks, structure learning, which consists of creating the structure of the Bayesian networks from the collected data, and parameter learning, which consists of calculating the numerical parameters for a given structure. We focus on the structure-learning problem of a flood decision supporting system. The algorithm WILD is used to discretize the continuous attributes in the flood database. The Bayesian network in the flood decision supporting system is obtained by K2. Explanations of the model are given. We describe an important process in exploiting decision supporting systems using Bayesian networks. It is shown that the model is correct and the Bayesian network is a good approach in a flood decision supporting system.","PeriodicalId":90702,"journal":{"name":"Proceedings. International Conference on Machine Learning and Cybernetics","volume":"19 1","pages":"718-722 vol.2"},"PeriodicalIF":0.0,"publicationDate":"2002-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73723383","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: 21
An operable and systemic approach to designing organizations 设计组织的可操作和系统的方法
Proceedings. International Conference on Machine Learning and Cybernetics Pub Date : 2002-11-04 DOI: 10.1109/ICMLC.2002.1174405
Dongsheng Yang, Zhong Liu, Weiming Zhang, Wen-wei Chen
{"title":"An operable and systemic approach to designing organizations","authors":"Dongsheng Yang, Zhong Liu, Weiming Zhang, Wen-wei Chen","doi":"10.1109/ICMLC.2002.1174405","DOIUrl":"https://doi.org/10.1109/ICMLC.2002.1174405","url":null,"abstract":"In this paper, we present a hierarchy hypothesis (HH) for designing organizations, and advance an operable and systemic approach based on HH to design organizations, which support the viable systems model and the methods of a three-phase iterative organizational design process and integrate the recursion and balance principle viable system model.","PeriodicalId":90702,"journal":{"name":"Proceedings. International Conference on Machine Learning and Cybernetics","volume":"106 1","pages":"596-600 vol.2"},"PeriodicalIF":0.0,"publicationDate":"2002-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73695064","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
Anti-control of chaos based on fuzzy neural networks inverse system method 基于模糊神经网络逆系统方法的混沌反控制
Proceedings. International Conference on Machine Learning and Cybernetics Pub Date : 2002-11-04 DOI: 10.1109/ICMLC.2002.1174491
H. Ren, Ding-I Liu
{"title":"Anti-control of chaos based on fuzzy neural networks inverse system method","authors":"H. Ren, Ding-I Liu","doi":"10.1109/ICMLC.2002.1174491","DOIUrl":"https://doi.org/10.1109/ICMLC.2002.1174491","url":null,"abstract":"The problem considered in the paper is anti-control of chaos for a non-chaotic system via a fuzzy neural network inverse system (FNNIS) method. A Sugeno type fuzzy neural network (FNN) is trained to learn the kinetics of the non-chaotic system. The trained FNN model is employed in the inverse system method, thereby, the exact mathematic model of the system to be controlled is not necessary. The FNN model error upon control is studied and a related theorem is developed. Simulation results for continuous and discrete systems show the effectiveness of the method.","PeriodicalId":90702,"journal":{"name":"Proceedings. International Conference on Machine Learning and Cybernetics","volume":"152 2","pages":"796-799 vol.2"},"PeriodicalIF":0.0,"publicationDate":"2002-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/ICMLC.2002.1174491","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72401247","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
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