{"title":"Application of adaptive fuzzy logic systems to model electric arc furnaces","authors":"A. Sadeghian, J. Lavers","doi":"10.1109/NAFIPS.1999.781815","DOIUrl":"https://doi.org/10.1109/NAFIPS.1999.781815","url":null,"abstract":"Presents the application of adaptive fuzzy logic systems to modelling electric arc furnaces. The main objectives are to provide the rationale and to justify the use of fuzzy modeling for electric furnaces. This is done with reference to three important properties of fuzzy logic systems, namely their nonlinear black-box modeling capability, universal approximation ability and their functional equivalence to radial basis function networks. A detailed investigation regarding the application of adaptive fuzzy logic systems to electric arc furnace modeling is presented. It is demonstrated that the application of adaptive fuzzy logic systems as a nonparametric system identification method to model nonlinear systems can be considered as an alternative to artificial neural networks. The proposed modeling methods are described, and their use is illustrated using actual recorded data.","PeriodicalId":335957,"journal":{"name":"18th International Conference of the North American Fuzzy Information Processing Society - NAFIPS (Cat. No.99TH8397)","volume":"44 7","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120908449","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}
{"title":"About the use of fuzzy clustering for texture classification","authors":"A. Stolpmann, L. Dooley","doi":"10.1109/NAFIPS.1999.781778","DOIUrl":"https://doi.org/10.1109/NAFIPS.1999.781778","url":null,"abstract":"This paper describes the use of a complex modular image processing system for texture classification. An introduction into problems that arise when handling textures is given. Furthermore the modules of the proposed system are described, namely the filtering and statistical modules, automatic feature vector optimization module and the classification module using clustering and fuzzy clustering methods. This texture classification system can easily be adapted for other tasks, including tasks in the field of medical imaging, remote sensing and quality control.","PeriodicalId":335957,"journal":{"name":"18th International Conference of the North American Fuzzy Information Processing Society - NAFIPS (Cat. No.99TH8397)","volume":"102 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121012856","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}
{"title":"Discussing cluster shapes of fuzzy classifiers","authors":"Andreas Nürnberger, A. Klose, Rudolf Kruse","doi":"10.1109/NAFIPS.1999.781753","DOIUrl":"https://doi.org/10.1109/NAFIPS.1999.781753","url":null,"abstract":"Fuzzy classification rules are widely considered a well-suited representation of classification knowledge, as they allow readable and interpretable rule bases. The goal of the paper is to discuss the shapes of the resulting classification borders and thus which class distributions can be represented by such classification systems. 2D and 3D visualizations are used to illustrate the cluster shapes and the borders between distinct classes. Furthermore, general hints concerning the shape of higher dimensional clusters are given.","PeriodicalId":335957,"journal":{"name":"18th International Conference of the North American Fuzzy Information Processing Society - NAFIPS (Cat. No.99TH8397)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122891259","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}
{"title":"Fuzzy measures for data quality","authors":"M. Janta-Polczynski, E. Roventa","doi":"10.1109/NAFIPS.1999.781722","DOIUrl":"https://doi.org/10.1109/NAFIPS.1999.781722","url":null,"abstract":"The aim of the paper is twofold: to introduce a clear and coherent framework of data as data elements-the building blocks of information systems; and to discuss dimensions of data quality along three axes: (a) quality of the conceptual view of data; (b) quality of the values to be stored in the database; (c) quality of the representation of data, i.e. their format. For each of these dimensions, the paper discusses the appropriateness of a representation in fuzzy logic.","PeriodicalId":335957,"journal":{"name":"18th International Conference of the North American Fuzzy Information Processing Society - NAFIPS (Cat. No.99TH8397)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128008470","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}
{"title":"Fuzzy models and potential outliers","authors":"M. Berthold","doi":"10.1109/NAFIPS.1999.781750","DOIUrl":"https://doi.org/10.1109/NAFIPS.1999.781750","url":null,"abstract":"Outliers or distorted attributes very often severely interfere with data analysis algorithms that try to extract few meaningful rules. Most methods to deal with outliers try to completely ignore them. This can be potentially harmful since the very outlier that was ignored might have described a rare but still extremely interesting phenomena. We describe an approach that tries to build an interpretable model while still maintaining all the information in the data. This is achieved through a two stage process. A first phase builds an outlier model for data points of low relevance, followed by a second stage which uses this model as filter and generates a simpler model, describing only examples with higher relevance, thus representing a more general concept. The outlier model on the other hand may point out potential areas of interest to the user. Preliminary experiments using an existing algorithm to construct fuzzy rule sets from data indicate that the two models in fact have lower complexity and sometimes even offer superior performance.","PeriodicalId":335957,"journal":{"name":"18th International Conference of the North American Fuzzy Information Processing Society - NAFIPS (Cat. No.99TH8397)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131873367","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}
{"title":"Adaptive image retrieval using the fuzzy integral","authors":"H. Frigui","doi":"10.1109/NAFIPS.1999.781759","DOIUrl":"https://doi.org/10.1109/NAFIPS.1999.781759","url":null,"abstract":"The paper proposes an alternative and iterative image retrieval system which takes into account the subjectivity of human perception of visual content. The proposed system uses a dynamic similarity measure based on the Choquet integral. Both positive and negative user's feedback are modeled by fuzzy sets, and are used to refine the feature relevance weights. The experimental results on more than 3000 texture images illustrate the learning behaviour of the retrieval system.","PeriodicalId":335957,"journal":{"name":"18th International Conference of the North American Fuzzy Information Processing Society - NAFIPS (Cat. No.99TH8397)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130330304","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}
{"title":"Intelligent adaptive control of robotic dynamic systems with a new hybrid neuro-fuzzy-fractal approach","authors":"O. Castillo, P. Melin","doi":"10.1109/NAFIPS.1999.781820","DOIUrl":"https://doi.org/10.1109/NAFIPS.1999.781820","url":null,"abstract":"We describe a new method for adaptive model based control of robotic dynamic systems using a new neuro fuzzy fractal approach. Intelligent control of robotic systems is a difficult problem because the dynamic of these systems is highly nonlinear. We describe an intelligent system for controlling robot manipulators to illustrate our neuro fuzzy fractal hybrid approach for adaptive control. We use a new fuzzy inference system for reasoning with multiple differential equations for model selection based on the relevant selection parameters for the problem. In this case, the fractal dimension of a time series of measured values of the variables is used as a selection parameter. We use neural networks for identification and control of robotic dynamic systems. The neural networks are trained with the Levenberg-Marquardt (LM) algorithm with real data to achieve the desired level of performance.","PeriodicalId":335957,"journal":{"name":"18th International Conference of the North American Fuzzy Information Processing Society - NAFIPS (Cat. No.99TH8397)","volume":"492 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115534110","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}
{"title":"Using t-norms in multi-objective analysis with fuzzy criteria","authors":"J. Ramík","doi":"10.1109/NAFIPS.1999.781790","DOIUrl":"https://doi.org/10.1109/NAFIPS.1999.781790","url":null,"abstract":"This paper deals with the generalized quasi-concavity based on triangular norms (t-norms) and applied to membership functions of fuzzy sets in n-dimensional Euclidean space. Necessary and sufficient conditions for this type of generalized quasi-concavity are derived, some examples demonstrating the concepts are presented and a possible application is discussed.","PeriodicalId":335957,"journal":{"name":"18th International Conference of the North American Fuzzy Information Processing Society - NAFIPS (Cat. No.99TH8397)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123719760","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}
{"title":"Lattice-theoretic properties of quasi-metric generating spaces","authors":"J. M. Barone","doi":"10.1109/NAFIPS.1999.781653","DOIUrl":"https://doi.org/10.1109/NAFIPS.1999.781653","url":null,"abstract":"There is more than one way to define a fuzzy metric space and to characterize the topologies generated by them. This paper discusses two varieties of fuzzy metric spaces and shows that they are equivalent with respect to the Vietoris topologies generated by the lattices of their open sets. In addition, a more general (fuzzier) variety of fuzzy metric spaces is introduced in which the open balls are delimited by fuzzy similitude. The relationships among these various versions of a fuzzy metric spaces are discussed, and the role of this more general fuzzy metric space as a generalization of the other varieties is explained.","PeriodicalId":335957,"journal":{"name":"18th International Conference of the North American Fuzzy Information Processing Society - NAFIPS (Cat. No.99TH8397)","volume":"665 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122967564","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}
{"title":"A passivity based stability analysis for a fuzzy PD+ control for robot manipulators","authors":"M. Llama, V. Santibáñez, J. Flores","doi":"10.1109/NAFIPS.1999.781777","DOIUrl":"https://doi.org/10.1109/NAFIPS.1999.781777","url":null,"abstract":"In this paper we present a passivity analysis for a motion control scheme, based on a fuzzy system for tuning the PD gains of the well known PD+ tracking controller for robot manipulators. We demonstrate, by exploiting the full nonlinear and multivariate nature of the robot's dynamics and its passivity property, that the overall closed loop system is asymptotically stable. In this control scheme, the fuzzy logic system plays the role of a tuner of the robot controller gains. We show that the closed loop system can be seen like two interconnected subsystems, where the nonlinear feedforward block is passive and the nonlinear feedback block is input strictly passive.","PeriodicalId":335957,"journal":{"name":"18th International Conference of the North American Fuzzy Information Processing Society - NAFIPS (Cat. No.99TH8397)","volume":"231 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122776079","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}