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Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference最新文献

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On fuzzy control of ventilation process in air-ventilated closed areas with emission of noxious gases 有害气体排放通风密闭区域通风过程的模糊控制
Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference Pub Date : 1994-06-26 DOI: 10.1109/FUZZY.1994.343721
M. Balazinski, E. Czogala, S. Kajl
{"title":"On fuzzy control of ventilation process in air-ventilated closed areas with emission of noxious gases","authors":"M. Balazinski, E. Czogala, S. Kajl","doi":"10.1109/FUZZY.1994.343721","DOIUrl":"https://doi.org/10.1109/FUZZY.1994.343721","url":null,"abstract":"This paper presents the idea of the application of a fuzzy logic controller to the control of a ventilation process in air-ventilated closed areas with emission of noxious gases. The results of the simulation of such a control using an approximate model of the process mentioned above are shown. The experiment indicates that the delay time in the inflow of fresh air causes unfading oscillations of the concentration of gases, which may exceed the admissible level.<<ETX>>","PeriodicalId":153967,"journal":{"name":"Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference","volume":"113 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120835024","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
Adaptive control of a class of nonlinear systems with fuzzy logic 一类非线性模糊系统的自适应控制
Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference Pub Date : 1994-06-26 DOI: 10.1109/FUZZY.1994.343834
C. Su, Y. Stepanenko
{"title":"Adaptive control of a class of nonlinear systems with fuzzy logic","authors":"C. Su, Y. Stepanenko","doi":"10.1109/FUZZY.1994.343834","DOIUrl":"https://doi.org/10.1109/FUZZY.1994.343834","url":null,"abstract":"An adaptive tracking control architecture is proposed for a class of continuous-time nonlinear dynamic systems, for which an explicit linear parameterization of the uncertainty in the dynamics is either unknown or impossible. The architecture employs fuzzy systems, which are expressed as a series expansion of basis functions, to adaptively compensate for the plant nonlinearities. Global asymptotic stability of the algorithm is established in the Lyapunov sense, with tracking errors converging to a neighborhood of zero. Simulation results for an unstable nonlinear plant are included to demonstrate that incorporating the linguistic fuzzy information from human experts results in superior tracking performance.<<ETX>>","PeriodicalId":153967,"journal":{"name":"Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121143915","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: 204
Two-pass orthogonal least-squares algorithm to train and reduce fuzzy logic systems 两步正交最小二乘算法训练和约简模糊逻辑系统
Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference Pub Date : 1994-06-26 DOI: 10.1109/FUZZY.1994.343651
J. Hohensohn, J. Mendel
{"title":"Two-pass orthogonal least-squares algorithm to train and reduce fuzzy logic systems","authors":"J. Hohensohn, J. Mendel","doi":"10.1109/FUZZY.1994.343651","DOIUrl":"https://doi.org/10.1109/FUZZY.1994.343651","url":null,"abstract":"Fuzzy logic systems (FLSs) can be designed using training data (i.e. given M numerical input/output pairs) and supervised learning algorithms. Orthogonal least-squares (OLS) learning decomposes a FLS into a linear combination of M/sub s/<M nonlinear fuzzy basis functions (FBFs), which are optimized during OLS to match the training data. The drawback to OLS is that the resulting system still contains information from all M initial rules, derived from the training points, even though only the most important M/sub s/ rules have been established by OLS. This is due to a normalization of the FBFs, and leads to excessive computation times during further processing. Our solution is to construct new FBFs out of the reduced rule-base and to run OLS a second time. The resulting system not only is of reduced computational complexity, but is of very similar behaviour to the unreduced system. The second run of OLS can be applied to a larger set of training data which greatly improves the precision. We illustrate our two-pass OLS algorithm for prediction of the Mackey-Glass chaotic time series.<<ETX>>","PeriodicalId":153967,"journal":{"name":"Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126584016","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
Intelligent adaptation of Kalman filters using fuzzy logic 基于模糊逻辑的卡尔曼滤波智能自适应
Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference Pub Date : 1994-06-26 DOI: 10.1109/FUZZY.1994.343829
J. Lalk
{"title":"Intelligent adaptation of Kalman filters using fuzzy logic","authors":"J. Lalk","doi":"10.1109/FUZZY.1994.343829","DOIUrl":"https://doi.org/10.1109/FUZZY.1994.343829","url":null,"abstract":"Significant benefits are to be found by dynamically adapting a Kalman filter state estimator if the noise conditions under which it operates change. It is traditional in adaptation schemes to adapt diagonal elements of the process noise covariance matrix, Q(n), or the measurement noise covariance matrix, R(n), or both. A novel adaptive scheme employing the principles of fuzzy expert systems is explored in this paper. The performance of the new scheme is compared with that of two traditional schemes.<<ETX>>","PeriodicalId":153967,"journal":{"name":"Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125698496","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
An approach to the evaluation of human resources by using fuzzy set theory 基于模糊集理论的人力资源评价方法
Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference Pub Date : 1994-06-26 DOI: 10.1109/FUZZY.1994.343899
A. Cannavacciuolo, G. Capaldo, A. Ventre, A. Volpe, G. Zollo
{"title":"An approach to the evaluation of human resources by using fuzzy set theory","authors":"A. Cannavacciuolo, G. Capaldo, A. Ventre, A. Volpe, G. Zollo","doi":"10.1109/FUZZY.1994.343899","DOIUrl":"https://doi.org/10.1109/FUZZY.1994.343899","url":null,"abstract":"This paper presents a method used to improve the current personnel evaluation procedures in a large company. The method is grounded on the semiotic analysis of stories justifying judgments. Categories and verbal values are represented by using concepts of fuzzy set theory. Particularly, a method is presented to measure the membership value of an individual in a predefined fuzzy category.<<ETX>>","PeriodicalId":153967,"journal":{"name":"Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125486409","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
A hybrid fuzzy/neural system used to extract heuristic knowledge from a fault detection problem 一种用于从故障检测问题中提取启发式知识的模糊/神经混合系统
Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference Pub Date : 1994-06-26 DOI: 10.1109/FUZZY.1994.343595
P. Goode, M. Chow
{"title":"A hybrid fuzzy/neural system used to extract heuristic knowledge from a fault detection problem","authors":"P. Goode, M. Chow","doi":"10.1109/FUZZY.1994.343595","DOIUrl":"https://doi.org/10.1109/FUZZY.1994.343595","url":null,"abstract":"Neural net have proven to be capable of solving the motor monitoring and fault detection problem using an inexpensive, reliable and noninvasive procedure. The neural net, unfortunately, cannot provide heuristic knowledge about the motor or the fault detection process. This paper introduces a novel hybrid fuzzy/neural fault detector that uses the learning capabilities of the neural net to detect if a motor has an incipient fault. Once the fuzzy/neural fault detector is trained, heuristic knowledge about the motor and the fault detection process can also be extracted. With better understanding of the heuristics through the use of fuzzy rules and fuzzy membership functions, we can have a better understanding of the fault detection process of the system; thus we can design better motor protection systems. The electric motors in industry are exposed to a wide variety of environments and conditions. These factors, coupled with the natural aging process of any machine, make the motor subject to incipient faults. These incipient faults, left undetected, contribute to the degradation and eventual failure of the motors. With proper monitoring and fault detection schemes, the incipient faults can be detected; thus maintenance and down-time expenses can be reduced while also improving safety. In this paper, motor bearing faults in single-phase induction motors are used to illustrate this novel system. This illustration demonstrates the successful training of a hybrid fuzzy/neural system that can provide accurate fault detection, and gives the heuristic reasoning for the fault detection procedure.<<ETX>>","PeriodicalId":153967,"journal":{"name":"Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128816952","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
Fuzzy logic control of non-minimum phase system 非最小相位系统的模糊逻辑控制
Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference Pub Date : 1994-06-26 DOI: 10.1109/FUZZY.1994.343686
Chin-Yin Tsai, T.-H.S. Li
{"title":"Fuzzy logic control of non-minimum phase system","authors":"Chin-Yin Tsai, T.-H.S. Li","doi":"10.1109/FUZZY.1994.343686","DOIUrl":"https://doi.org/10.1109/FUZZY.1994.343686","url":null,"abstract":"An fuzzy logic controller (FLC) is developed in this paper for the nonminimum phase system. The well-designed fuzzy rules are exploited to resolve the undershoot problem caused by the unstable zeros. A 3rd-order plant with two unstable zeros is used to verify the performance of the fuzzy controlled system. Simulations demonstrate that the proposed fuzzy logic controller can be used to handle the nonminimum phase system.<<ETX>>","PeriodicalId":153967,"journal":{"name":"Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference","volume":"72 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127341736","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
A fuzzy chip-based real-time fault classifier in a power controller 基于模糊芯片的电源控制器实时故障分类器
Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference Pub Date : 1994-06-26 DOI: 10.1109/FUZZY.1994.343920
Xing Wu, C. Wu
{"title":"A fuzzy chip-based real-time fault classifier in a power controller","authors":"Xing Wu, C. Wu","doi":"10.1109/FUZZY.1994.343920","DOIUrl":"https://doi.org/10.1109/FUZZY.1994.343920","url":null,"abstract":"A fuzzy chip-based electrical power faults classifier is presented in this paper. The system, which utilizes a fuzzy chip designed for the fuzzy rule base inference, detects the faults in the electrical power system in real time and activates the circuit control unit to take the appropriate actions. A set of features are extracted, and two sets of fuzzy inference rules are used to classify faults based on those features. The membership functions for all fuzzy variables are trained based on a supervised learning algorithm. Features extracted from structure properties of the patterns enable the classifier to rapidly detect the faults appearing in electrical power within 50 /spl mu/s. The fuzzy chip, in this fault classifier, provides speed and cost improvement over the existing general-purpose microprocessor technologies,.<<ETX>>","PeriodicalId":153967,"journal":{"name":"Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference","volume":"138 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132622488","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
Fuzzy decision trees by fuzzy ID3 algorithm and its application to diagnosis systems 模糊ID3算法的模糊决策树及其在诊断系统中的应用
Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference Pub Date : 1994-06-26 DOI: 10.1109/FUZZY.1994.343539
M. Umanol, H. Okamoto, I. Hatono, H. Tamura, F. Kawachi, S. Umedzu, J. Kinoshita
{"title":"Fuzzy decision trees by fuzzy ID3 algorithm and its application to diagnosis systems","authors":"M. Umanol, H. Okamoto, I. Hatono, H. Tamura, F. Kawachi, S. Umedzu, J. Kinoshita","doi":"10.1109/FUZZY.1994.343539","DOIUrl":"https://doi.org/10.1109/FUZZY.1994.343539","url":null,"abstract":"A popular and particularly efficient method for making a decision tree for classification from symbolic data is ID3 algorithm. Revised algorithms for numerical data have been proposed, some of which divide a numerical range into several intervals or fuzzy intervals. Their decision trees, however, are not easy to understand. We propose a new version of ID3 algorithm to generate an understandable fuzzy decision tree using fuzzy sets defined by a user. We apply it to diagnosis for potential transformers by analyzing gas in oil.<<ETX>>","PeriodicalId":153967,"journal":{"name":"Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122195735","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: 269
Linearity and the cnf property in linear fuzzy rule interpolation 线性模糊规则插值中的线性与cnf性质
Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference Pub Date : 1994-06-26 DOI: 10.1109/FUZZY.1994.343850
L. Kóczy, S. Kovács
{"title":"Linearity and the cnf property in linear fuzzy rule interpolation","authors":"L. Kóczy, S. Kovács","doi":"10.1109/FUZZY.1994.343850","DOIUrl":"https://doi.org/10.1109/FUZZY.1994.343850","url":null,"abstract":"It is an important question if rule interpolation is done whether the theoretical shape of the membership function of the calculated conclusion is exactly or approximately linear between two neighboring /spl alpha/-levels in the breakpoint set, or it has a very different shape. In the latter case, interpolation for only a few (as e.g. 0 and 1) levels is not satisfactory, which fact might increase the computational time necessary for generating the conclusion by a large constant factor. It is also examined if the conclusion has a convex and normal membership function, i.e. whether the calculated infima exceed the calculated suprema of the given /spl alpha/-cut or not.<<ETX>>","PeriodicalId":153967,"journal":{"name":"Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130679176","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: 18
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