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Third International Conference on Industrial Fuzzy Control and Intelligent Systems最新文献

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A hybrid architecture for predicting oil slick movement 预测浮油移动的混合体系结构
Third International Conference on Industrial Fuzzy Control and Intelligent Systems Pub Date : 1993-12-01 DOI: 10.1109/IFIS.1993.324180
Haojin Wang, J. Wolter, Jungfu Tsao
{"title":"A hybrid architecture for predicting oil slick movement","authors":"Haojin Wang, J. Wolter, Jungfu Tsao","doi":"10.1109/IFIS.1993.324180","DOIUrl":"https://doi.org/10.1109/IFIS.1993.324180","url":null,"abstract":"In this paper, we present a hybrid architecture for an intelligent system that can be used to project oil slick movement. The system under construction has the ability to learn from historical weather data and then to incorporate the learned knowledge into its projection of the future movement of oil slick. It employs probabilistic reasoning to deal with uncertainty in the observed data and weather forecast, neural networks to acquire knowledge from historical data and fuzzy logic to deal with imprecision embedded in the available information. This innovative approach to this highly complicated, but very important and practical issue exemplifies the application of advanced AI techniques to the practical problems.<<ETX>>","PeriodicalId":408138,"journal":{"name":"Third International Conference on Industrial Fuzzy Control and Intelligent Systems","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1993-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127902556","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
Simulation studies of fuzzy clustering in the context of brain magnetic resonance imaging 脑磁共振成像中模糊聚类的仿真研究
Third International Conference on Industrial Fuzzy Control and Intelligent Systems Pub Date : 1993-12-01 DOI: 10.1109/IFIS.1993.324188
M. E. Brandt, Y.F. Kharas
{"title":"Simulation studies of fuzzy clustering in the context of brain magnetic resonance imaging","authors":"M. E. Brandt, Y.F. Kharas","doi":"10.1109/IFIS.1993.324188","DOIUrl":"https://doi.org/10.1109/IFIS.1993.324188","url":null,"abstract":"An important problem in segmentation of brain magnetic resonance images (MRI) is partial volume averaging of different types of tissue. This manifests itself as an overlap of tissue groups in the image histogram space. Fuzzy clustering is an effective technique for separating groups having vague boundaries. The fuzzy C-means (FCM) algorithm has been used for this purpose yet its effectiveness in discerning group differences on the order of a few percent in MRIs is not known. In this report, we compare the effectiveness of the hard C-means, several variants of FCM, and three versions of a possibilistic clustering approach in separating three simulated clusters as boundary overlap is increased.<<ETX>>","PeriodicalId":408138,"journal":{"name":"Third International Conference on Industrial Fuzzy Control and Intelligent Systems","volume":"298 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1993-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131426134","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
Design and performance of CMOS analog fuzzy chips CMOS模拟模糊芯片的设计与性能
Third International Conference on Industrial Fuzzy Control and Intelligent Systems Pub Date : 1993-12-01 DOI: 10.1109/IFIS.1993.324194
K. Shono, C. Pham
{"title":"Design and performance of CMOS analog fuzzy chips","authors":"K. Shono, C. Pham","doi":"10.1109/IFIS.1993.324194","DOIUrl":"https://doi.org/10.1109/IFIS.1993.324194","url":null,"abstract":"A new approach for implementing a CMOS analog fuzzy processor under the conventional Si wafer processing of the CMOS digital LSI is described. The membership function generator circuit which plays a very important role in the proposed processor has been studied, The defuzzyfication of the combined inference results was performed in the outside digital circuit. The dynamic behavior of fuzzy logic control was visualized on a PC display to evaluate the performance.<<ETX>>","PeriodicalId":408138,"journal":{"name":"Third International Conference on Industrial Fuzzy Control and Intelligent Systems","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1993-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122000414","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
Fuzzy modelling of machine-tool cutting process 机床切削过程的模糊建模
Third International Conference on Industrial Fuzzy Control and Intelligent Systems Pub Date : 1993-12-01 DOI: 10.1109/IFIS.1993.324189
E. Aguero, J. R. Alique, R. Haber, C. Rodriguez
{"title":"Fuzzy modelling of machine-tool cutting process","authors":"E. Aguero, J. R. Alique, R. Haber, C. Rodriguez","doi":"10.1109/IFIS.1993.324189","DOIUrl":"https://doi.org/10.1109/IFIS.1993.324189","url":null,"abstract":"Fuzzy control of machining process is a very promissory approach, taking into account the machine-tool complexity and efficiency. Creation of the knowledge base for this fuzzy controller requires something more than operators experience: an objective support. Such objective support is to be obtained from experiments, during which the machine-tool actually performs the cutting process and the corresponding input and output data must be gathered. A rather efficient approach, fuzzy clustering, was chosen for elaborating this data in order to obtain the required knowledge base for the fuzzy model. The paper describes the algorithms, experiments and fuzzy models for the cutting process of a milling machine. The models obtained are the basis for designing the model-based fuzzy supervisory controller for this machine.<<ETX>>","PeriodicalId":408138,"journal":{"name":"Third International Conference on Industrial Fuzzy Control and Intelligent Systems","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1993-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121362996","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
Customer-adaptive fuzzy control of home heating system 家庭供暖系统的用户自适应模糊控制
Third International Conference on Industrial Fuzzy Control and Intelligent Systems Pub Date : 1993-12-01 DOI: 10.1109/IFIS.1993.324203
C. V. Altrock, H.-O. Arend, B. Krause, C. Steffens, E. Behrens-Rommler
{"title":"Customer-adaptive fuzzy control of home heating system","authors":"C. V. Altrock, H.-O. Arend, B. Krause, C. Steffens, E. Behrens-Rommler","doi":"10.1109/IFIS.1993.324203","DOIUrl":"https://doi.org/10.1109/IFIS.1993.324203","url":null,"abstract":"To maximize both heating economy and comfort of a private home heating system, fuzzy-logic control has been used by a German company in a new generation of furnace controllers. The controller ensures optimal customer heating demands while using one sensor less than the former generation. Both the fuzzy-logic controller and the conventional control system were implemented on a standard 8-bit microcontroller. The design, optimization and implementation of the fuzzy controller was supported by the software development system fuzzy TECH.<<ETX>>","PeriodicalId":408138,"journal":{"name":"Third International Conference on Industrial Fuzzy Control and Intelligent Systems","volume":"142 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1993-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123219684","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
A method for automatic generation of a fuzzy model 一种自动生成模糊模型的方法
Third International Conference on Industrial Fuzzy Control and Intelligent Systems Pub Date : 1993-12-01 DOI: 10.1109/IFIS.1993.324208
J. Yen, H. Wang, J. Liao
{"title":"A method for automatic generation of a fuzzy model","authors":"J. Yen, H. Wang, J. Liao","doi":"10.1109/IFIS.1993.324208","DOIUrl":"https://doi.org/10.1109/IFIS.1993.324208","url":null,"abstract":"The goal of this research is to develop a method to automate the process of fuzzy model construction. The method we developed extends the existing methods and is based on a combination of genetic algorithms and statistic techniques. The preliminary testing shows that it has the advantages of implementation simplicity, a short training cycle and simple resulting fuzzy model.<<ETX>>","PeriodicalId":408138,"journal":{"name":"Third International Conference on Industrial Fuzzy Control and Intelligent Systems","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1993-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114268171","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: 11
Fusion ARTMAP: an adaptive fuzzy network for multi-channel classification 融合ARTMAP:一种多通道分类的自适应模糊网络
Third International Conference on Industrial Fuzzy Control and Intelligent Systems Pub Date : 1993-12-01 DOI: 10.1109/IFIS.1993.324195
Yousif R. Asfour, G. Carpenter, S. Grossberg, G. Lesher
{"title":"Fusion ARTMAP: an adaptive fuzzy network for multi-channel classification","authors":"Yousif R. Asfour, G. Carpenter, S. Grossberg, G. Lesher","doi":"10.1109/IFIS.1993.324195","DOIUrl":"https://doi.org/10.1109/IFIS.1993.324195","url":null,"abstract":"Fusion ARTMAP is a self-organizing neural network architecture for multi-channel, or multi-sensor, data fusion. Fusion ARTMAP generalizes the fuzzy ARTMAP architecture in order to adaptively classify multi-channel data. The network has a symmetric organization such that each channel can be dynamically configured to serve as either a data input or a teaching input to the system. An ART module forms a compressed recognition code within each channel. These codes, in turn, become inputs to a single ART system that organizes the global recognition code. When a predictive error occurs, a process called parallel match tracking simultaneously raises vigilances in multiple ART modules until reset is triggered in one of them. Parallel match tracking hereby resets only that portion of the recognition code with the poorest match, or minimum predictive confidence. This internally-controlled selective reset process is a type of credit assignment that creates a parsimoniously connected learned network.<<ETX>>","PeriodicalId":408138,"journal":{"name":"Third International Conference on Industrial Fuzzy Control and Intelligent Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1993-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125806872","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
Stability analysis of nonlinear fuzzy PI control systems 非线性模糊PI控制系统的稳定性分析
Third International Conference on Industrial Fuzzy Control and Intelligent Systems Pub Date : 1993-12-01 DOI: 10.1109/IFIS.1993.324200
Guanrong Chen, H. Ying
{"title":"Stability analysis of nonlinear fuzzy PI control systems","authors":"Guanrong Chen, H. Ying","doi":"10.1109/IFIS.1993.324200","DOIUrl":"https://doi.org/10.1109/IFIS.1993.324200","url":null,"abstract":"In this paper, we analyze the stability of nonlinear fuzzy PI (proportional-integral) control systems. The fuzzy PI controller involved is actually a nonlinear adaptive PI controller whose gains change continuously with output of the processes under control. We have employed the \"small gain theorem\" to obtain a simple sufficient condition for the global asymptotic stability of the nonlinear fuzzy PI control systems. In addition, we have proven that in a conventional PI control system, if the linear PI controller is replaced by the nonlinear fuzzy PI controller, then the stability of the resulting control system remains unchanged. This result is true no matter the given process is linear or not. We have also derived explicit formulas for the computation of the fuzzy PI controller parameters, using only the proportional and integral gains of the corresponding linear PI controller.<<ETX>>","PeriodicalId":408138,"journal":{"name":"Third International Conference on Industrial Fuzzy Control and Intelligent Systems","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1993-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131293762","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: 58
On local and fuzzy modelling 局部和模糊建模
Third International Conference on Industrial Fuzzy Control and Intelligent Systems Pub Date : 1993-12-01 DOI: 10.1109/IFIS.1993.324209
B. A. Foss, T.A. Johansen
{"title":"On local and fuzzy modelling","authors":"B. A. Foss, T.A. Johansen","doi":"10.1109/IFIS.1993.324209","DOIUrl":"https://doi.org/10.1109/IFIS.1993.324209","url":null,"abstract":"Modelling methods that support different levels of accuracy and tolerate large variations in process knowledge are discussed within the framework of local modelling and fuzzy modelling. It is shown that local modelling can be viewed as an extension of earlier work within fuzzy modelling.<<ETX>>","PeriodicalId":408138,"journal":{"name":"Third International Conference on Industrial Fuzzy Control and Intelligent Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1993-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129251096","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: 29
A fuzzy logic based controller for a three link manipulator 基于模糊逻辑的三连杆机械臂控制器
Third International Conference on Industrial Fuzzy Control and Intelligent Systems Pub Date : 1993-12-01 DOI: 10.1109/IFIS.1993.324204
B. Pate, G. Langari
{"title":"A fuzzy logic based controller for a three link manipulator","authors":"B. Pate, G. Langari","doi":"10.1109/IFIS.1993.324204","DOIUrl":"https://doi.org/10.1109/IFIS.1993.324204","url":null,"abstract":"This paper addresses the task of producing a generic control algorithm for Cartesian motion of manipulators. The algorithm employs a self organizing fuzzy logic estimator to produce joint space changes given Cartesian error. The main focus of this work is to investigate the performance of the algorithm around the workspace and conclude the feasibility of such an algorithm in industrial applications.<<ETX>>","PeriodicalId":408138,"journal":{"name":"Third International Conference on Industrial Fuzzy Control and Intelligent Systems","volume":"83 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1993-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116136468","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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