{"title":"Robustness of interval type-2 fuzzy logic systems","authors":"M. Biglarbegian, W. Melek, J. Mendel","doi":"10.1109/NAFIPS.2010.5548209","DOIUrl":"https://doi.org/10.1109/NAFIPS.2010.5548209","url":null,"abstract":"Fuzzy logic systems (FLSs) have been successfully used in various modeling and control applications. More importantly, we are witnessing an increasing interest in using interval type-2 FLSs (IT2 FLSs) for numerous applications. However, robustness, defined as the tolerance of an FLS to handle a maximum desired output deviation, is not usually considered in the design process of FLSs, and hence there is a need for an in-depth investigation. In this paper, we present a methodology for the robustness analysis of IT2 FLSs. Our approach is general and can be used to analyze the robustness of T1 FLSs as well. To demonstrate the effectiveness of the proposed methodologies, two examples are presented, and it is concluded that T1 and IT2 FLSs exhibit robust behaviors. Moreover, IT2 FLSs due to their flexible structures, revealed reduced output errors and in some cases showed enhanced robust performance than T1. In general, the superiority in terms of the robust performance of T1 over IT2 (or IT2 over T1) is problem-dependent. The approach presented in this paper can be exploited in the design of robust FLSs for modeling applications.","PeriodicalId":394892,"journal":{"name":"2010 Annual Meeting of the North American Fuzzy Information Processing Society","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117135211","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":"Introducing strong T-transitivity in approximate fuzzy preorders and equivalences","authors":"D. Boixader, J. Recasens","doi":"10.1109/NAFIPS.2010.5548261","DOIUrl":"https://doi.org/10.1109/NAFIPS.2010.5548261","url":null,"abstract":"Any fuzzy preorder or equivalence is or is not a fuzzy preorder or equivalence. Through these pages we present two ways of regarding any arbitrary fuzzy relation as a fuzzy preorder or equivalence, at least to some extent. The two ways are the axiomatic approach, wich deals with relaxed versions of reflexivity, symmetry and T-transitivity, and the similarity based approach, which looks into the proximity between a given arbitrary relation and a prototype – a fuzzy preorder or equivalence in the standard fuzzy sense. The relationship between the two views on the problem is studied. As a result, strong-T-transitivity is introduced and shown to be a more suitable choice than standard T-transitivity.","PeriodicalId":394892,"journal":{"name":"2010 Annual Meeting of the North American Fuzzy Information Processing Society","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116278078","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}
A. Mansour, H. Ying, P. Dews, Yanqing Ji, M.S. Farber, J. Yen, Richard E. Miller, R. Massanari
{"title":"A multi-agent system for detecting adverse drug reactions","authors":"A. Mansour, H. Ying, P. Dews, Yanqing Ji, M.S. Farber, J. Yen, Richard E. Miller, R. Massanari","doi":"10.1109/NAFIPS.2010.5548293","DOIUrl":"https://doi.org/10.1109/NAFIPS.2010.5548293","url":null,"abstract":"Discovering unknown adverse drug reactions (ADRs) as early as possible is highly desirable. Current methods largely rely on passive spontaneous reports, which suffer from serious underreporting, latency, and inconsistent reporting. They are not ideal for early identification of ADRs [5]. In this paper, we propose a multi-agent system approach for ADR detection. A multi-agent system is formed by a community of agents that exchange information and proactively help one another to achieve the goals set by the system designer. We show how agents, equipped with decision rules developed by the physicians on the team, can collaborate to detect signal pairs of potential ADRs. Using the popular agent language JADE [8, 10] and clinical information on 1,000 patients treated at the Detroit Veterans Affairs Medical Center, we have constructed a small group of agents and generated preliminary simulated detection results.","PeriodicalId":394892,"journal":{"name":"2010 Annual Meeting of the North American Fuzzy Information Processing Society","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122649565","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 division of bipolar fuzzy relations","authors":"P. Bosc, O. Pivert","doi":"10.1109/NAFIPS.2010.5548260","DOIUrl":"https://doi.org/10.1109/NAFIPS.2010.5548260","url":null,"abstract":"In this paper, we deal with the relational division operation and extend it so that it can handle bipolar fuzzy relations, i.e., relations where each tuple t is attached a pair of grades in the unit interval expressing the extent to which t satisfies a flexible constraint and a flexible wish tied by a consistency condition. The framework considered is that of an extended relational algebra. It is shown that the result of a division of bipolar relations can be characterized as a twofold quotient. The question of the (non-) primitivity of the operator is also tackled.","PeriodicalId":394892,"journal":{"name":"2010 Annual Meeting of the North American Fuzzy Information Processing Society","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122898735","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":"New incremental fuzzy c medoids clustering algorithms","authors":"Nicolas Labroche","doi":"10.1109/NAFIPS.2010.5548263","DOIUrl":"https://doi.org/10.1109/NAFIPS.2010.5548263","url":null,"abstract":"This paper proposes two new incremental fuzzy c medoids clustering algorithms for very large datasets. These algorithms are tailored to work with continuous data streams, where all the data is not necessarily available at once or can not fit in main memory. Some fuzzy algorithms already propose solutions to manage large datasets in a similar way but are generally limited to spatial datasets to avoid the complexity of medoids computation. Our methods keep the advantages of the fuzzy approaches and add the capability to handle large relational datasets by considering the continuous input stream of data as a set of data chunks that are processed sequentially. Two distinct models are proposed to aggregate the information discovered from each data chunk and produce the final partition of the dataset. Our new algorithms are compared to state-of-the-art fuzzy clustering algorithms on artificial and real datasets. Experiments show that our new approaches perform closely if not better than existing algorithms while adding the capability to handle relational data to better match the needs of real world applications.","PeriodicalId":394892,"journal":{"name":"2010 Annual Meeting of the North American Fuzzy Information Processing Society","volume":"95 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115794952","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":"An application of fuzzy number to educational evaluation method","authors":"Hsunhsun Chung, T. Takizawa","doi":"10.1109/NAFIPS.2010.5548210","DOIUrl":"https://doi.org/10.1109/NAFIPS.2010.5548210","url":null,"abstract":"It is known that approximate reasoning can be applied to educational evaluation. Especially, evaluation of works in calligraphy and drawing can be obtained more effectively using the approximate reasoning evaluation method than using the weighted mean evaluation method, and the authors use an example to explain why grading by approximate reasoning is more appropriate for grading creative work than grading by weighted mean. In this paper, the authors also propose a method of applying fuzzy numbers to educational evaluation in order to make approximate reasoning more generally applicable and also discuss the properties of the results.","PeriodicalId":394892,"journal":{"name":"2010 Annual Meeting of the North American Fuzzy Information Processing Society","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115969383","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":"Artificial adaptive systems and predictive medicine","authors":"E. Grossi, M. Buscema","doi":"10.1109/NAFIPS.2010.5548296","DOIUrl":"https://doi.org/10.1109/NAFIPS.2010.5548296","url":null,"abstract":"An individual patient is not the average representative of the population. Rather he or she is a person with unique characteristics. An intervention may be effective for a population but not necessarily for the individual patient. The recommendation of a guideline may not be right for a particular patient because it is not what he or she wants, and implementing the recommendation will not necessarily mean a favourable outcome. The author describes a reconfiguration of medical thought which originates from non linear dynamics and chaos theory. The coupling of computer science and these new theoretical bases coming from complex systems mathematics allows the creation of “intelligent” agents able to adapt themselves dynamically to problem of high complexity: the Artificial Adaptive Systems, which include Artificial Neural Networks (ANNs) and Evolutionary Algorithms (EA). ANNs and EA are able to reproduce the dynamical interaction of multiple factors simultaneously, allowing the study of complexity; they can also help medical doctors in making decisions under extreme uncertainty and to draw conclusions on individual basis and not as average trends.","PeriodicalId":394892,"journal":{"name":"2010 Annual Meeting of the North American Fuzzy Information Processing Society","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121917730","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 direct solution for obtaining a priority vector from interval pairwise comparison matrix","authors":"Kuo-Ping Chiao","doi":"10.1109/NAFIPS.2010.5548206","DOIUrl":"https://doi.org/10.1109/NAFIPS.2010.5548206","url":null,"abstract":"A direct solution based on graphical method([9]) for linear programming with two decision variables for finding the interval priority vector in interval Analytic Hierarchy Pro-cess(AHP) is introduced in this paper. Instead of performing complicated computations, the graphical approach is developed to find the global optimal solution to the mathematical programming model for priority vector for the interval pairwise comparison matrix. The solution from graphical method is the global extremes rather than the local extremes. As a result the normalized optimal priority vector is referred to as the Global Optimal Interval Priority Vector (GOIPV). To verify GOIPV method, a numerical example from literature is reviewed with GOIPV method.","PeriodicalId":394892,"journal":{"name":"2010 Annual Meeting of the North American Fuzzy Information Processing Society","volume":"72 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131723251","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 difference of intervals and differentiability of interval-valued functions","authors":"Y. Chalco-Cano, W. Lodwick","doi":"10.1109/NAFIPS.2010.5548176","DOIUrl":"https://doi.org/10.1109/NAFIPS.2010.5548176","url":null,"abstract":"In this article we present different approaches to the difference of two intervals and its application to differentiability of interval-valued functions. Also, we show the relationship between some definitions of derivative for interval-valued functions.","PeriodicalId":394892,"journal":{"name":"2010 Annual Meeting of the North American Fuzzy Information Processing Society","volume":"148 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129108011","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 new meta-classifier","authors":"M. Buscema, W. J. Tastle","doi":"10.1109/NAFIPS.2010.5548298","DOIUrl":"https://doi.org/10.1109/NAFIPS.2010.5548298","url":null,"abstract":"A taxonomy for classifying classifiers is presented. A new meta-classifier, Meta-Consensus, with a foundation in both consensus theory and the theory of independent judges, is introduced.","PeriodicalId":394892,"journal":{"name":"2010 Annual Meeting of the North American Fuzzy Information Processing Society","volume":"272 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124402406","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}