{"title":"Modeling the real world for data mining: granular computing approach","authors":"T.Y. Lin, E. Louie","doi":"10.1109/NAFIPS.2001.943713","DOIUrl":"https://doi.org/10.1109/NAFIPS.2001.943713","url":null,"abstract":"In logic, a \"real world\" is modeled by a Cantor set with relational structure. In this paper, the relational structure is confined to the simplest kind, namely, binary relations. From different consideration, in granular computing, such a binary relational structure has been called a crisp/fuzzy binary granulation, or binary neighborhood system (FBNS). Intuitively, the set has been granulated into binary neighborhoods (generalized equivalence classes). Combining the two views, the simplest kind of \"real world\" model is BNS-space. From this view, the classical relational theory is the knowledge representation of the universe whose structure is a finite set of equivalence relations; in a \"real world\" relational theory, a finite set of crisp/fuzzy binary relations. Here knowledge representation is assigning meaningful names to binary neighborhoods (or equivalence classes in relational theory). Depending on the structures, the model can be useful in fuzzy logic or data mining. The focus of this paper is on data mining using granular computing. Experiments show that the computing is extremely fast and the cost of computing extra semantics is very small.","PeriodicalId":227374,"journal":{"name":"Proceedings Joint 9th IFSA World Congress and 20th NAFIPS International Conference (Cat. No. 01TH8569)","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126467170","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":"Stability of slowly varying Takagi-Sugeno fuzzy systems","authors":"R. Pytelková, P. Hušek","doi":"10.1109/NAFIPS.2001.944256","DOIUrl":"https://doi.org/10.1109/NAFIPS.2001.944256","url":null,"abstract":"Presents a method for analyzing the stability of slowly varying Takagi-Sugeno fuzzy systems with linear submodels in the consequents of rules. This method can be used for both continuous-time and discrete-time systems and is based on transformation of the problem of stability of Takagi-Sugeno fuzzy systems to the problem of stability of polynomials with coefficients polynomically depending on weights of rules. It is supposed that the plant is described by the Takagi-Sugeno fuzzy system with linear state-space or input-output submodels in the consequents of rules and the controller by the Takagi-Sugeno fuzzy system with linear state feedback submodels or dynamic output feedback controllers in the consequents of rules. The problem of the stability analysis of such systems can be transformed to the problem of the stability analysis of polynomials with polynomic structure of its coefficients. This problem can be solved by the modified Jury (for discrete-time systems) or by the modified Routh or Hurwitz criterion (for continuous-time systems).","PeriodicalId":227374,"journal":{"name":"Proceedings Joint 9th IFSA World Congress and 20th NAFIPS International Conference (Cat. No. 01TH8569)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121111264","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":"Multiobjective fuzzy random linear programming using E-model and possibility measure","authors":"H. Katagiri, M. Sakawa, H. Ishii","doi":"10.1109/NAFIPS.2001.944430","DOIUrl":"https://doi.org/10.1109/NAFIPS.2001.944430","url":null,"abstract":"The authors deal with multiobjective linear programming problems with fuzzy random variable coefficients. Since the problem is ill-defined due to both fuzziness and randomness, we propose a decision making model based on E-model, which is a useful model in stochastic programming, and a possibility measure. First, we show that the formulated problem is reduced to a multiobjective linear fractional programming problem. After defining a Pareto optimal solution based on the expected value of possibility measure, we construct a solution algorithm for solving a minimax problem. Further, we consider interactive decision making using reference points and give numerical examples.","PeriodicalId":227374,"journal":{"name":"Proceedings Joint 9th IFSA World Congress and 20th NAFIPS International Conference (Cat. No. 01TH8569)","volume":"87 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116085717","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":"Life long learning and adaptation for embedded agents operating in unstructured environments","authors":"H. Hagras, M. Colley, V. Callaghan","doi":"10.1109/NAFIPS.2001.943779","DOIUrl":"https://doi.org/10.1109/NAFIPS.2001.943779","url":null,"abstract":"The authors introduce a novel technique for lifelong learning and adaptation of mobile robotic agents operating in unstructured environments based on our patented fuzzy-genetic system (British patent 99-10539.7). The life long learning strategy tunes the controllers learnt in our previous work by a process of gradual improvement and adaptation to the surrounding environment. We have applied this work to two different unstructured environments: the agricultural environment and the intelligent buildings environment.","PeriodicalId":227374,"journal":{"name":"Proceedings Joint 9th IFSA World Congress and 20th NAFIPS International Conference (Cat. No. 01TH8569)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121031152","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":"Case-base reduction using learned local feature weights","authors":"Eric C. C. Tsang, S. Shiu, X.Z. Wang, K. Ho","doi":"10.1109/NAFIPS.2001.943699","DOIUrl":"https://doi.org/10.1109/NAFIPS.2001.943699","url":null,"abstract":"Case-base reasoning (CBR) systems making use of previous cases to solve new, unseen and different problems have drawn great attention in recent years. It is true that the number of cases stored in the case library of a CBR system is directly related to the retrieval efficiency. Although more cases in the library can improve the coverage of the problem space, the system performance will be downgraded if the size of the library grows to an unacceptable level. The paper addresses the problem of case base maintenance by developing a method to reduce the size of large case libraries so as to improve the efficiency while maintaining the accuracy of the CBR system. To achieve this, we adopt the local feature weights approach. This approach consists of three phases. The first phase involves partitioning the case-base into different clusters. The second phase involves learning the optimal local feature weights for each case and the final phase involves reducing the case-base based on the optimal local weights. The paper focuses on the last two phases. To justify the usefulness of the method, we perform an experiment which uses efficiency, competence, and ability to solve new problems as the benchmark to verify our design.","PeriodicalId":227374,"journal":{"name":"Proceedings Joint 9th IFSA World Congress and 20th NAFIPS International Conference (Cat. No. 01TH8569)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121216240","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":"Incremental mining of association patterns on compressed data","authors":"V. Ng, Jacky Man-Lee Wong, Paul Bao","doi":"10.1109/NAFIPS.2001.944293","DOIUrl":"https://doi.org/10.1109/NAFIPS.2001.944293","url":null,"abstract":"Introducing data compression concept to large databases has been proposed for many years. In this project, we propose a new algorithm for the compression of large databases. Our goal is to optimize the I/O effort for finding association rules. The algorithm partitions the databases into two parts and all transactions will be compressed with the help of a reference transaction found in the small partition. We also compared the proposed compression algorithms with a normal compression algorithm - the binary compression. Empirical evaluation shows that the proposed algorithm performs well both in reducing the storage space and the I/O process required to find the large item sets for association rules.","PeriodicalId":227374,"journal":{"name":"Proceedings Joint 9th IFSA World Congress and 20th NAFIPS International Conference (Cat. No. 01TH8569)","volume":"43 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116735298","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":"Fast fuzzy clustering of infrared images","authors":"S. Eschrich, Jingwei Ke, L. Hall, D. Goldgof","doi":"10.1109/NAFIPS.2001.944766","DOIUrl":"https://doi.org/10.1109/NAFIPS.2001.944766","url":null,"abstract":"Clustering is an important technique for unsupervised image segmentation. The use of fuzzy c-means clustering can provide more information and better partitions than traditional c-means. In image processing, the ability to reduce the precision of the input data and aggregate similar examples can lead to significant data reduction and correspondingly less execution time. This paper discusses brFCM (bit reduction by Fuzzy C-Means), a data reduction fuzzy c-means clustering algorithm. The algorithm is described and several key implementation issues are discussed. Performance speedup and correspondence to a typical FCM implementation are presented from a data set of 172 infrared images. Average speedups of 59 times that of traditional FCM were obtained using brFCM, while producing identical cluster output relative to FCM.","PeriodicalId":227374,"journal":{"name":"Proceedings Joint 9th IFSA World Congress and 20th NAFIPS International Conference (Cat. No. 01TH8569)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121691029","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":"Renewal of the causes by observed effects by means of fuzzy relations matrix and genetic algorithm","authors":"A. Rotshtein, H. Rakytyanska","doi":"10.1109/NAFIPS.2001.944688","DOIUrl":"https://doi.org/10.1109/NAFIPS.2001.944688","url":null,"abstract":"Application of inverse logical inference in diagnostic expert systems is considered. Diagnosis decision finding requires fuzzy logical equation system solutions. The genetic algorithm for optimization based on crossover, mutation and selection of the initial set of chromosomes is proposed for fuzzy logical equation system solving. Computer simulation illustrates the algorithm efficiency. The suggested genetic algorithm can find application in expert systems for technical and medical diagnosis and quality control.","PeriodicalId":227374,"journal":{"name":"Proceedings Joint 9th IFSA World Congress and 20th NAFIPS International Conference (Cat. No. 01TH8569)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123872177","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":"Active power line conditioner optimum placement using fuzzy controller","authors":"M. Kalantar","doi":"10.1109/NAFIPS.2001.944259","DOIUrl":"https://doi.org/10.1109/NAFIPS.2001.944259","url":null,"abstract":"Application of APLC to minimize the load harmonic distortion in the power system is one of the most effective and useful techniques to conflict with harmonics. Previous papers on APLC focuses largely on minimizing harmonic voltage distortions across an entire network by using properly located APLC. This paper discusses the optimum placing of an APLC into the power system by designing a fuzzy system. The fuzzy system designed is very useful for this purpose. Optimal placing of an APLC not only depends on topology of network, constrained injection current and kind of objective functions but also depends mostly on the experiences obtained from an expert person and his ability to know the network. Application of fuzzy system having advantages of using fuzzy experiences are wide in the area of control theory and power system planning. Results of an fuzzy system designed to be used in active power systems are presented in this paper.","PeriodicalId":227374,"journal":{"name":"Proceedings Joint 9th IFSA World Congress and 20th NAFIPS International Conference (Cat. No. 01TH8569)","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121396328","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":"On the absolute stability of the single-input fuzzy logic controller","authors":"Byung-Jae Choi","doi":"10.1109/NAFIPS.2001.943731","DOIUrl":"https://doi.org/10.1109/NAFIPS.2001.943731","url":null,"abstract":"Much research has been introduced to decrease the number of parameters representing the antecedent part of the fuzzy control rule. We briefly explain a single-input fuzzy logic controller (SFLC) which uses only a single input variable. We analyze whether it is absolutely stable based on the sector bounded condition. We also show the feasibility of the proposed stability analysis through a numerical example of a mass-damper-spring system.","PeriodicalId":227374,"journal":{"name":"Proceedings Joint 9th IFSA World Congress and 20th NAFIPS International Conference (Cat. No. 01TH8569)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125146433","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}