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NAFIPS 2007 - 2007 Annual Meeting of the North American Fuzzy Information Processing Society最新文献

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Using 2-Interactive Measures in Nonlinear Classifications 非线性分类中的2-交互测度
NAFIPS 2007 - 2007 Annual Meeting of the North American Fuzzy Information Processing Society Pub Date : 2007-06-24 DOI: 10.1109/NAFIPS.2007.383863
Yan Wu, Zhenyuan Wang
{"title":"Using 2-Interactive Measures in Nonlinear Classifications","authors":"Yan Wu, Zhenyuan Wang","doi":"10.1109/NAFIPS.2007.383863","DOIUrl":"https://doi.org/10.1109/NAFIPS.2007.383863","url":null,"abstract":"Within the classification algorithms based on signed fuzzy measures, an obvious limitation is the complexity of the algorithms due to the large number of interactions among attributes. For a data set with n attributes, the complexity of classification algorithm would be O (2n). But in the practical problems, the higher-order interactions among attributes are often not significant enough to the classification. So sometimes omitting them just sacrifices the accuracy a little but will save a lot of time and energy. Hence, a 2-interactive measure may be used to reduce the calculation complexity into O (n2). In this study, the Mobius Transformation and its reverse - Zeta Transformation are used to calculate the 2-interactions among attributes for the records. A comprehensive discussion on the semantic and geometric meanings of the parameters is given. The weighted Choquet integral with respect to a signed fuzzy measure serves as an aggregation tool to project the feature space onto a real axis to make the classification simple. To implement the classification, we need to determine the values of the signed fuzzy measure and the other parameters. This can be done by running an adaptive genetic algorithm based on a given training data set. The new classifier is tested by recovering the preset parameters from a set of artificial training data generated from these parameters.","PeriodicalId":292853,"journal":{"name":"NAFIPS 2007 - 2007 Annual Meeting of the North American Fuzzy Information Processing Society","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117177627","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
Genetic Multivariable PID Controller Based on IMC 基于IMC的遗传多变量PID控制器
NAFIPS 2007 - 2007 Annual Meeting of the North American Fuzzy Information Processing Society Pub Date : 2007-06-24 DOI: 10.1109/NAFIPS.2007.383832
Sharareh Kermanshachi, N. Sadati
{"title":"Genetic Multivariable PID Controller Based on IMC","authors":"Sharareh Kermanshachi, N. Sadati","doi":"10.1109/NAFIPS.2007.383832","DOIUrl":"https://doi.org/10.1109/NAFIPS.2007.383832","url":null,"abstract":"A new approach for PID tuning, based on GA (Genetic algorithm) and Internal Model Control (IMC) technique, is presented in this paper. PID tuning is based on using Method. The IMC technique reduces the number of parameters that must be tuned for a multivariable system using PID controller. The algorithm uses GA for optimal determination of IMC variables. Simulation results present the good performance of the proposed method.","PeriodicalId":292853,"journal":{"name":"NAFIPS 2007 - 2007 Annual Meeting of the North American Fuzzy Information Processing Society","volume":"131 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124145491","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
Fuzzy Boolean Nets Based Paediatrics First Aid Diagnosis 基于模糊布尔网的儿科急救诊断
NAFIPS 2007 - 2007 Annual Meeting of the North American Fuzzy Information Processing Society Pub Date : 2007-06-24 DOI: 10.1109/NAFIPS.2007.383916
Joao Paulo Carvalho, N. Horta, J. Tomé
{"title":"Fuzzy Boolean Nets Based Paediatrics First Aid Diagnosis","authors":"Joao Paulo Carvalho, N. Horta, J. Tomé","doi":"10.1109/NAFIPS.2007.383916","DOIUrl":"https://doi.org/10.1109/NAFIPS.2007.383916","url":null,"abstract":"This paper proposes the use of Fuzzy Boolean Nets to implement a home paediatrics first-aid diagnosis expert system which goal is to counsel what actions should a parent take based on the symptoms exhibited by a child.","PeriodicalId":292853,"journal":{"name":"NAFIPS 2007 - 2007 Annual Meeting of the North American Fuzzy Information Processing Society","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115404867","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
Parallel Evolutionary Computing using a cluster for Mathematical Function Optimization 基于聚类的并行进化计算数学函数优化
NAFIPS 2007 - 2007 Annual Meeting of the North American Fuzzy Information Processing Society Pub Date : 2007-06-24 DOI: 10.1109/NAFIPS.2007.383908
F. Valdez, P. Melin
{"title":"Parallel Evolutionary Computing using a cluster for Mathematical Function Optimization","authors":"F. Valdez, P. Melin","doi":"10.1109/NAFIPS.2007.383908","DOIUrl":"https://doi.org/10.1109/NAFIPS.2007.383908","url":null,"abstract":"In this paper the optimization of complex mathematical functions is studied, applying evolutionary computing methods (particle swarm optimization and genetic algorithms), with the purpose of finding the global minimum of a search space. The simulations of PSO and GAs were made in a cluster of computers, with the purpose of distributing the function in several processors (slaves) and to gather results in the master.","PeriodicalId":292853,"journal":{"name":"NAFIPS 2007 - 2007 Annual Meeting of the North American Fuzzy Information Processing Society","volume":"135 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132598203","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
Neighbourhood Sets based on Web Usage Mining 基于Web使用挖掘的邻域集
NAFIPS 2007 - 2007 Annual Meeting of the North American Fuzzy Information Processing Society Pub Date : 2007-06-24 DOI: 10.1109/NAFIPS.2007.383919
P. Lingras
{"title":"Neighbourhood Sets based on Web Usage Mining","authors":"P. Lingras","doi":"10.1109/NAFIPS.2007.383919","DOIUrl":"https://doi.org/10.1109/NAFIPS.2007.383919","url":null,"abstract":"Hyperlink structure of a Web site can be improved based on the Web usage information. Creating adaptive Web sites based on Web usage mining is receiving increasing interest from the researchers. It is important to develop theoretical frameworks for such a research. This paper discusses how neighbourhood sets can be a useful framework for analyzing Web access sequences.","PeriodicalId":292853,"journal":{"name":"NAFIPS 2007 - 2007 Annual Meeting of the North American Fuzzy Information Processing Society","volume":"206 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114369200","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
Design an Intelligent Neural-Fuzzy Controller for Hybrid Motorcycle 混合动力摩托车智能神经模糊控制器设计
NAFIPS 2007 - 2007 Annual Meeting of the North American Fuzzy Information Processing Society Pub Date : 2007-06-24 DOI: 10.1109/NAFIPS.2007.383852
Yao-Lun Liu, Chia-Chang Tong, Wu-Shun Jwo, Shuen-Jeng Lin
{"title":"Design an Intelligent Neural-Fuzzy Controller for Hybrid Motorcycle","authors":"Yao-Lun Liu, Chia-Chang Tong, Wu-Shun Jwo, Shuen-Jeng Lin","doi":"10.1109/NAFIPS.2007.383852","DOIUrl":"https://doi.org/10.1109/NAFIPS.2007.383852","url":null,"abstract":"The main propose of this article is to design an intelligent neural-fuzzy controller for hybrid motorcycle. A self-tuning PID tracking controller based on RBF neural network with Fuzzy current limiter is proposed to maneuver the motor and save some energy in hybrid mode. The outer motor control loop is designed to track down the speed fluctuations by Neural-PID controller. Besides, one inner loop is designed to limit the armature current whenever the power demand is diminished according to a set of Fuzzy rules. The proposed structure is put into tests by Matlab programming. Simulations confirm this RBF-PID controller with Fuzzy current limiter can save 23.5% energy for a tracking task.","PeriodicalId":292853,"journal":{"name":"NAFIPS 2007 - 2007 Annual Meeting of the North American Fuzzy Information Processing Society","volume":"15 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114383443","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: 16
Sepsis and Septic Shock Analysis using Neural Networks 用神经网络分析脓毒症和感染性休克
NAFIPS 2007 - 2007 Annual Meeting of the North American Fuzzy Information Processing Society Pub Date : 2007-06-24 DOI: 10.1109/NAFIPS.2007.383917
C. Schuh
{"title":"Sepsis and Septic Shock Analysis using Neural Networks","authors":"C. Schuh","doi":"10.1109/NAFIPS.2007.383917","DOIUrl":"https://doi.org/10.1109/NAFIPS.2007.383917","url":null,"abstract":"After major surgery many patients develop signs and symptoms of generalized inflammation, which is defined as Systemic Inflammatory Response Syndrome (SIRS). To examine the systemic inflammatory response syndrome in the intensive care unit (ICU) after cardiac and thoracic surgery a retrospective study was performed on 1674 selected patients admitted in the Cardiothoracic ICU of the University Hospital of Vienna. SIRS was defined according to the American College of Chest Physicians / Society of Critical Care Medicine (ACCP / SCCM) Consensus Conference. The term's SIRS, sepsis, septic shock and MODS (multi organ dysfunction syndrome) are used to describe the different extents of inflammation and infections. In the first phase the moment of the first occurrence of SIRS, and of severe SIRS was determined. An SIRS episode was defined as a time interval from the beginning of SIRS until the receding of the symptoms for more than 24 hours. Based on this information, an artificial neural network (ANN) was constructed to predict severe SIRS. SIRS was present in 1544 patients (92.2%), SIRS with additional signs of organ dysfunction evolving in 76.1% of the cases; the progression took less than 24 hours in 87.9% of the cases. The presence of signs of the SIRS on the first operative day is hardly suitable for the risk prediction. A significant correlation between the number of SIRS episodes and the outcome for each individual patient was found. The number of SIRS episodes could be an accurate parameter for estimating the outcome and the treatment outlay.","PeriodicalId":292853,"journal":{"name":"NAFIPS 2007 - 2007 Annual Meeting of the North American Fuzzy Information Processing Society","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123854277","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: 12
Investigating Learning Methods for Binary Data 研究二进制数据的学习方法
NAFIPS 2007 - 2007 Annual Meeting of the North American Fuzzy Information Processing Society Pub Date : 2007-06-24 DOI: 10.1109/NAFIPS.2007.383880
S. Visa, A. Ralescu, M. Ionescu
{"title":"Investigating Learning Methods for Binary Data","authors":"S. Visa, A. Ralescu, M. Ionescu","doi":"10.1109/NAFIPS.2007.383880","DOIUrl":"https://doi.org/10.1109/NAFIPS.2007.383880","url":null,"abstract":"Michie et al. show in [1] that decision trees perform better than twenty other classification algorithms in classifying binary data. In this paper we further investigate this hypothesis by comparing the decision trees with a fuzzy set-based classifier and the naive Bayes on real and artificial datasets.","PeriodicalId":292853,"journal":{"name":"NAFIPS 2007 - 2007 Annual Meeting of the North American Fuzzy Information Processing Society","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128991569","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
Contingency Table and Granularity 列联表和粒度
NAFIPS 2007 - 2007 Annual Meeting of the North American Fuzzy Information Processing Society Pub Date : 2007-06-24 DOI: 10.1109/NAFIPS.2007.383920
S. Tsumoto, S. Hirano
{"title":"Contingency Table and Granularity","authors":"S. Tsumoto, S. Hirano","doi":"10.1109/NAFIPS.2007.383920","DOIUrl":"https://doi.org/10.1109/NAFIPS.2007.383920","url":null,"abstract":"This paper gives a matrix-theory based approach to a contingency table and shows that sample size gives a strong constraints on its granularity. In the former studies, relations between degree of granularity and dependence of contingency tables are given from the viewpoint of determinantal divisors and sample size. The nature of determinantal divisors shows that the increase of the degree of granularity may lead to that of dependence. However, a constraint on the sample size of a contingency table is very strong, which leads to the evaluation formula where the increase of degree of granularity gives the decrease of dependency. This paper gives a further study of the nature of sample size effect on the degree of dependency in a contingency matrix. The results show that sample size will restrict the nature of matrix in a combinatorial way, which suggests that the dependency is closely related with integer programming.","PeriodicalId":292853,"journal":{"name":"NAFIPS 2007 - 2007 Annual Meeting of the North American Fuzzy Information Processing Society","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129861495","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
Modular Neural Networks and Type-2 Fuzzy Logic for Face Recognition 模块化神经网络与2型模糊逻辑在人脸识别中的应用
NAFIPS 2007 - 2007 Annual Meeting of the North American Fuzzy Information Processing Society Pub Date : 2007-06-24 DOI: 10.1109/NAFIPS.2007.383912
O. Mendoza, Guillermo Licea, P. Melin
{"title":"Modular Neural Networks and Type-2 Fuzzy Logic for Face Recognition","authors":"O. Mendoza, Guillermo Licea, P. Melin","doi":"10.1109/NAFIPS.2007.383912","DOIUrl":"https://doi.org/10.1109/NAFIPS.2007.383912","url":null,"abstract":"In this paper we present a method for face recognition combining modular neural networks and two interval type-2 fuzzy inference systems (FIS 2) for face recognition. The first FIS 2 is used for edges detection in the training data, and the second one to find the ideal parameters for the Sugeno integral as a decision operator. Fuzzy logic is shown to be a tool that can help improve the results of a neural system facilitating the representation of the human perception.","PeriodicalId":292853,"journal":{"name":"NAFIPS 2007 - 2007 Annual Meeting of the North American Fuzzy Information Processing Society","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130159979","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
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