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

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On learning control knowledge for a HTN-POP hybrid planner HTN-POP混合规划器控制知识的学习
Proceedings. International Conference on Machine Learning and Cybernetics Pub Date : 2002-11-04 DOI: 10.1109/ICMLC.2002.1175368
S. Fernández, R. Aler, D. Borrajo
{"title":"On learning control knowledge for a HTN-POP hybrid planner","authors":"S. Fernández, R. Aler, D. Borrajo","doi":"10.1109/ICMLC.2002.1175368","DOIUrl":"https://doi.org/10.1109/ICMLC.2002.1175368","url":null,"abstract":"In this paper we present a learning method that is able to automatically acquire control knowledge for a hybrid HTN-POP planner called HYBIS. HYBIS decomposes a problem in subproblems using either a default method or a user-defined decomposition method. Then, at each level of abstraction, it generates a plan at that level using a POCL (Partial Order Causal Link) planning technique. Our learning approach builds on HAMLET, a system that learns control knowledge for a total order non-linear planner (PRODIGY4.0). In this paper, we focus on the operator selection problem for the POP component of HYBIS, which is very important for efficiency purposes.","PeriodicalId":90702,"journal":{"name":"Proceedings. International Conference on Machine Learning and Cybernetics","volume":"94 1","pages":"1899-1904 vol.4"},"PeriodicalIF":0.0,"publicationDate":"2002-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81799186","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
A novel watermarking for images using neural networks 一种基于神经网络的图像水印算法
Proceedings. International Conference on Machine Learning and Cybernetics Pub Date : 2002-11-04 DOI: 10.1109/ICMLC.2002.1167437
Jun Zhang, Nengchao Wang, Feng Xiong
{"title":"A novel watermarking for images using neural networks","authors":"Jun Zhang, Nengchao Wang, Feng Xiong","doi":"10.1109/ICMLC.2002.1167437","DOIUrl":"https://doi.org/10.1109/ICMLC.2002.1167437","url":null,"abstract":"Watermarking, which can be applied to the copyright protection and the integrity of multimedia products, has recently become a very active area of research. This paper proposes a novel watermarking scheme for an image. The image is firstly decomposed by multiwavelet transformation, and then the relation among subblocks in the coarsest level of the multiwavelet domain is learned by a back-propagation neural network, which is trained using coefficients in three subblocks as input vectors and corresponding coefficients in another sub-block as output values. Finally a logo watermark is embedded into the multiwavelet domain by adjusting the relation among these subblocks. Experimental results show that the proposed method is superior to the similar one in the literature.","PeriodicalId":90702,"journal":{"name":"Proceedings. International Conference on Machine Learning and Cybernetics","volume":"109 1","pages":"1405-1408 vol.3"},"PeriodicalIF":0.0,"publicationDate":"2002-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80838750","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
Chinese part of speech tagging based on maximum entropy method 基于最大熵法的汉语词性标注
Proceedings. International Conference on Machine Learning and Cybernetics Pub Date : 2002-11-04 DOI: 10.1109/ICMLC.2002.1167446
Hong Ling, Chun-Fa Yuan
{"title":"Chinese part of speech tagging based on maximum entropy method","authors":"Hong Ling, Chun-Fa Yuan","doi":"10.1109/ICMLC.2002.1167446","DOIUrl":"https://doi.org/10.1109/ICMLC.2002.1167446","url":null,"abstract":"A lot of researches have been made on the application of the maximum entropy modeling in natural language processing in recent years. In this paper, we present a new Chinese part of speech tagging method based on the maximum entropy principle because Chinese language is quite different from many other languages. The feature selection is the key point in our system, which is distinct from the one used in English. Experiment results show that the part of speech tagging accuracy ratio of our system is up to 97.34%.","PeriodicalId":90702,"journal":{"name":"Proceedings. International Conference on Machine Learning and Cybernetics","volume":"367 1","pages":"1447-1450 vol.3"},"PeriodicalIF":0.0,"publicationDate":"2002-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77794318","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: 6
GA-based object recognition in a complex noisy environment 复杂噪声环境下基于遗传算法的目标识别
Proceedings. International Conference on Machine Learning and Cybernetics Pub Date : 2002-11-04 DOI: 10.1109/ICMLC.2002.1167478
J. Xin, Ding Liu, Han Liu, Yanxi Yang
{"title":"GA-based object recognition in a complex noisy environment","authors":"J. Xin, Ding Liu, Han Liu, Yanxi Yang","doi":"10.1109/ICMLC.2002.1167478","DOIUrl":"https://doi.org/10.1109/ICMLC.2002.1167478","url":null,"abstract":"This paper describes a method for object recognition in a complex noisy environment based on the genetic algorithm (GA). A small object is represented by their binary edges. A fitness function is constructed by the shape of an object in combination with its frame model to search for the position and orientation of the target in the input image. In order to enhance the orientation function of the fitness function, some preprocessing operations have been done. The simulation result shows that the method presented is effective and has great practical value.","PeriodicalId":90702,"journal":{"name":"Proceedings. International Conference on Machine Learning and Cybernetics","volume":"43 1","pages":"1586-1589 vol.3"},"PeriodicalIF":0.0,"publicationDate":"2002-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82368387","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: 6
The design and analysis on a new type of fuzzy controller 一种新型模糊控制器的设计与分析
Proceedings. International Conference on Machine Learning and Cybernetics Pub Date : 2002-11-04 DOI: 10.1109/ICMLC.2002.1175422
Chao-ying Liu, Xue-ling Song
{"title":"The design and analysis on a new type of fuzzy controller","authors":"Chao-ying Liu, Xue-ling Song","doi":"10.1109/ICMLC.2002.1175422","DOIUrl":"https://doi.org/10.1109/ICMLC.2002.1175422","url":null,"abstract":"Based on analyzing the effect of the scaling factors of a fuzzy controller on system performance, the paper proposes a new type of fuzzy controller with nonlinear scaling functions and discusses its effect on membership functions, equivalent mapping between input and output parameter, nonlinear surface for the controller and system performance in detail. Besides the parts mentioned above, the paper also studies the relationship of the parameters in nonlinear scaling functions and system performance. The parameter design of the fuzzy controller with nonlinear scaling functions is simple and normalization is also easy for online learning and adjustment in an adaptive fuzzy controller. Simulation result shows that compared with a conventional fuzzy controller, this controller with nonlinear scaling function has better dynamic and static properties, and it is a simple, useful and effective method for improving the fuzzy controller properties.","PeriodicalId":90702,"journal":{"name":"Proceedings. International Conference on Machine Learning and Cybernetics","volume":"123 1","pages":"2165-2170 vol.4"},"PeriodicalIF":0.0,"publicationDate":"2002-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80922288","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
Self-learning error compensation in CNC grinding 数控磨削中的自学习误差补偿
Proceedings. International Conference on Machine Learning and Cybernetics Pub Date : 2002-11-04 DOI: 10.1109/ICMLC.2002.1174542
X. Tian, Bo Peng, Qing Xu
{"title":"Self-learning error compensation in CNC grinding","authors":"X. Tian, Bo Peng, Qing Xu","doi":"10.1109/ICMLC.2002.1174542","DOIUrl":"https://doi.org/10.1109/ICMLC.2002.1174542","url":null,"abstract":"In this paper, a new intelligent self-learning error compensation algorithm for CNC grinding of ceramic chips is introduced. In the process of ceramic chip computer numeric control (CNC) grinding, the dimension of the chip tends to get larger and the dimensional error to exceed the tolerance as the number of the machined chips accumulates. There are many factors leading to the occurrence of the error and the law of error variation is very complicated. With an introduced the intelligent self-learning error compensation technique, the CNC system can improve the control strategy to compensate the error automatically. The simulation result shows the effectiveness of this algorithm.","PeriodicalId":90702,"journal":{"name":"Proceedings. International Conference on Machine Learning and Cybernetics","volume":"36 1","pages":"1044-1047 vol.2"},"PeriodicalIF":0.0,"publicationDate":"2002-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83225494","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
Low state-space complexity and high coverage Markov browsing forecast 低状态空间复杂度和高覆盖率马尔可夫浏览预测
Proceedings. International Conference on Machine Learning and Cybernetics Pub Date : 2002-11-04 DOI: 10.1109/ICMLC.2002.1174553
Dongshan Xing, Jun-Yi Shen
{"title":"Low state-space complexity and high coverage Markov browsing forecast","authors":"Dongshan Xing, Jun-Yi Shen","doi":"10.1109/ICMLC.2002.1174553","DOIUrl":"https://doi.org/10.1109/ICMLC.2002.1174553","url":null,"abstract":"Browsing the World Wide Web (WWW) involves traversing hyperlink connections among documents. The ability to forecast browsing patterns can solve many problems that face producers and consumers of WWW content. Although Markov models have been found well suited to forecasting browsing modes, they have some drawbacks. To solve them, we present a new model, Markov tree model (MTM), to forecast user-browsing modes. It aggregates user-browsing information by a tree. By this structure, a forecast model can't generate an explosive number of states. All the forecast process can be performed on the MTM. During the forecast procedure, a recursive process is adopted to handle the problem of low coverage. If a higher sequence can't get a result, a lower sequence may be used. Experiments confirm that MTM can get higher coverage and lower state complexity. It can be widely used in prefetching, link prediction and recommendation, etc.","PeriodicalId":90702,"journal":{"name":"Proceedings. International Conference on Machine Learning and Cybernetics","volume":"85 1","pages":"1093-1097 vol.2"},"PeriodicalIF":0.0,"publicationDate":"2002-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82737579","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
Study of bifurcation in current-controlling DC/DC converters 电流控制DC/DC变换器的分岔研究
Proceedings. International Conference on Machine Learning and Cybernetics Pub Date : 2002-11-04 DOI: 10.1109/ICMLC.2002.1175388
J. Zhang, Xue-Ye Wei
{"title":"Study of bifurcation in current-controlling DC/DC converters","authors":"J. Zhang, Xue-Ye Wei","doi":"10.1109/ICMLC.2002.1175388","DOIUrl":"https://doi.org/10.1109/ICMLC.2002.1175388","url":null,"abstract":"Begins with a description of the chaotic dynamics and bifurcation scenarios observed in power electronics circuits. Simple boost DC/DC converters are used as representative examples to illustrate the modeling approaches that are capable of retaining the essential qualitative properties. Furthermore, we present a detailed discussion of the modeling methods to explain nonlinear phenomena such as bifurcation and chaos with nonlinear method.","PeriodicalId":90702,"journal":{"name":"Proceedings. International Conference on Machine Learning and Cybernetics","volume":"26 24 1","pages":"2005-2009 vol.4"},"PeriodicalIF":0.0,"publicationDate":"2002-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90957214","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
Stock market time series data mining based on regularized neural network and rough set 基于正则化神经网络和粗糙集的股票市场时间序列数据挖掘
Proceedings. International Conference on Machine Learning and Cybernetics Pub Date : 2002-11-04 DOI: 10.1109/ICMLC.2002.1176765
Xiao-ye Wang, Zheng-ou Wang
{"title":"Stock market time series data mining based on regularized neural network and rough set","authors":"Xiao-ye Wang, Zheng-ou Wang","doi":"10.1109/ICMLC.2002.1176765","DOIUrl":"https://doi.org/10.1109/ICMLC.2002.1176765","url":null,"abstract":"Presents a method of stock market time series data mining, which combines a regularized neural network with rough sets. The process includes preprocessing of a time series database and data mining. The preprocessing cleans and filters time series. Then, we partition the time series into a series of static patterns, which is based on the trend (i.e., increasing or decreasing) of the closing price. An information table is formed by the most important predictable attributes and target attributes identified from each pattern. The regularized neural network (RNN) is used to study and predict the data. Rough sets can extract rule knowledge in the trained neural network that can be used to predict the time series behavior in the future. The method combines the high generalization faculty of the regularized neural network and the rule reduction capability of rough sets. An experiment demonstrates the effectiveness of the algorithm.","PeriodicalId":90702,"journal":{"name":"Proceedings. International Conference on Machine Learning and Cybernetics","volume":"25 1","pages":"315-318 vol.1"},"PeriodicalIF":0.0,"publicationDate":"2002-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91258009","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: 17
SLMBSVMs: a structural-loss-minimization-based support vector machines approach slmbsvm:基于结构损失最小化的支持向量机方法
Proceedings. International Conference on Machine Learning and Cybernetics Pub Date : 2002-11-04 DOI: 10.1109/ICMLC.2002.1167448
Liang Zhang, Shui Yu, Yunming Ye, Fanyuan Ma
{"title":"SLMBSVMs: a structural-loss-minimization-based support vector machines approach","authors":"Liang Zhang, Shui Yu, Yunming Ye, Fanyuan Ma","doi":"10.1109/ICMLC.2002.1167448","DOIUrl":"https://doi.org/10.1109/ICMLC.2002.1167448","url":null,"abstract":"Existing approaches,for constructing SVMs are based on minimization of structural risk where the generalization error loss is treated equivalently for each training pattern. Considering that error loss of one pattern is generally different to the other's in real binary classification problems, we propose a reformulation of the minimization problem such that generalization error rate for-each training pattern are treated respectively to minimize total generalization loss, which we call the structural-loss-minimization-based support vector machines (SLMBSVM). We. show experimentally that SLMBSVMs is potential.","PeriodicalId":90702,"journal":{"name":"Proceedings. International Conference on Machine Learning and Cybernetics","volume":"31 1","pages":"1455-1459 vol.3"},"PeriodicalIF":0.0,"publicationDate":"2002-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89418640","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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