{"title":"Queries mixing positive and negative associations and their weakening","authors":"P. Bosc, O. Pivert","doi":"10.1109/NAFIPS.2010.5548287","DOIUrl":"https://doi.org/10.1109/NAFIPS.2010.5548287","url":null,"abstract":"This paper deals with queries involving two components: one describing desired associations, another specifying forbidden associations. In addition, those preferences are cited in the context of a hierarchy expressing some strength about what is wanted and rejected. So doing an ordinal ordering over the answers is made available in order to distinguish among the elements of the answer. The situation where no answer is returned is also tackled and it is proposed to soften the initial query in order to get a non-empty answer. It is shown that this can be achieved still using an ordinal framework which is an extension of the initial one.","PeriodicalId":394892,"journal":{"name":"2010 Annual Meeting of the North American Fuzzy Information Processing Society","volume":"308 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":"125767563","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 uninorm-based neuron model and fuzzy neural networks","authors":"A. Lemos, W. Caminhas, F. Gomide","doi":"10.1109/NAFIPS.2010.5548195","DOIUrl":"https://doi.org/10.1109/NAFIPS.2010.5548195","url":null,"abstract":"This paper suggests a uninorm-based neuron model and a neural network architecture using unineurons. The unineuron generalizes logical and/or neurons using weighted uninorms. Previous works have addressed fuzzy neurons within the framework of uninorms. This paper introduces a new unineuron model that uses weighted aggregation of the inputs, and computes its output using a conventional neuron. A feedforward fuzzy neural architecture is developed and used to model nonlinear dynamic systems. The resulting fuzzy neural network easily allows fuzzy rule insertion and/or extraction from its topology, process information following a fuzzy inference mechanism, and is an universal function approximator. Experimental results show that the uninorm-based network provides accurate results and performs better than several similar neural and alternative fuzzy function approximators.","PeriodicalId":394892,"journal":{"name":"2010 Annual Meeting of the North American Fuzzy Information Processing Society","volume":"24 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":"125961476","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":"Activation and competition system and universe lines algorithm","authors":"M. Buscema, P. Sacco","doi":"10.1109/NAFIPS.2010.5548301","DOIUrl":"https://doi.org/10.1109/NAFIPS.2010.5548301","url":null,"abstract":"The Activation and Competition System (ACS), developed by Buscema in 2009 is an original algorithm that can simulate a non linear associative memory, partially inspired by Grossberg's IAC is presented. The Universe Lines Algorithm (ULA) is an extension of ACS and developed in 2010. ULA is able to transform all the variables of an assigned dataset into a group of connected dynamical systems.","PeriodicalId":394892,"journal":{"name":"2010 Annual Meeting of the North American Fuzzy Information Processing Society","volume":"60 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":"125564564","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 concept lattices: Examples using the Gene Ontology","authors":"V. Cross, M. Kandasamy, Wenting Yi","doi":"10.1109/NAFIPS.2010.5548196","DOIUrl":"https://doi.org/10.1109/NAFIPS.2010.5548196","url":null,"abstract":"Much research in the use of concept lattices for knowledge discovery and data mining has occurred in the past several years. Various approaches have also been proposed to create fuzzy formal contexts and to transform these into fuzzy concept lattices. This paper first briefly reviews concept lattices and then presents several approaches to creating fuzzy concept lattices. One of these approaches is demonstrated with bioinformatics data, specifically using gene annotation data files. The evidence code specified with an annotation is translated into a numeric value in (0, 1] and is interpreted as the degree of association between the gene or gene product and the annotating Gene Ontology term. These degrees of association are used to create the fuzzy formal context which can then be used to create a fuzzy concept lattice.","PeriodicalId":394892,"journal":{"name":"2010 Annual Meeting of the North American Fuzzy Information Processing Society","volume":"303 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":"114383798","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":"Extended Chebyshev type inequality for Sugeno integral","authors":"H. Román-Flores, A. Flores-Franulic, H. Agahi","doi":"10.1109/NAFIPS.2010.5548189","DOIUrl":"https://doi.org/10.1109/NAFIPS.2010.5548189","url":null,"abstract":"An extended Chebyshev type inequality for the Sugeno integral on abstract spaces is studied. More precisely, necessary and sufficient conditions under which the inequality, ∫<inf>A</inf>Φ(f ⋆ g)dµ ≥ (∫<inf>A</inf>Φ(f)dµ) ⋆ (∫<inf>A</inf> Φ(g)dµ) or its reverse hold for an arbitrary fuzzy measure-based type Sugeno integral µ and a binary operation ⋆: [0, ∞)<sup>2</sup> → [0, ∞) and a nonnegative function Φ : [0, ∞) → [0, ∞), are given.","PeriodicalId":394892,"journal":{"name":"2010 Annual Meeting of the North American Fuzzy Information Processing Society","volume":"427 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":"115931696","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 approach for channel equalization using quasi type-2 fuzzy systems","authors":"Luis F. Albarracin, M. Melgarejo","doi":"10.1109/NAFIPS.2010.5548203","DOIUrl":"https://doi.org/10.1109/NAFIPS.2010.5548203","url":null,"abstract":"This article presents a simple approach for the equalization of a nonlinear time varying communication channel using a quasi type-2 fuzzy system. Basically, the Quasi-type 2 fuzzy equalizer is tuned by clustering the output of the channel as it is proposed in previous reported works for other fuzzy equalizers. The main difference is that the quasi type-2 fuzzy perspective permits to derive more design parameters from clustering. The proposed equalizer is compared with type one and interval type-2 equalizers. Although, simulation results show that the quasi type-2 fuzzy adaptive filter exhibits better performance for particular levels of uncertainty, it behaves similarly to the other equalizers in general terms.","PeriodicalId":394892,"journal":{"name":"2010 Annual Meeting of the North American Fuzzy Information Processing Society","volume":"34 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":"116144991","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":"Degree-based ideas and technique can facilitate inter-disciplinary collaboration and education","authors":"Paulo Pinheiro da Silva, A. Velasco, O. Kosheleva","doi":"10.1109/NAFIPS.2010.5548212","DOIUrl":"https://doi.org/10.1109/NAFIPS.2010.5548212","url":null,"abstract":"In many application areas, there is a need for inter-disciplinary collaboration and education. However, such collaboration and education are not easy. On the example of our participation in a cyberinfrastructure project, we show that many obstacles on the path to successful collaboration and education can be overcome if we take into account that each person's knowledge of a statement is often a matter of degree – and that we can therefore use appropriate degree-based ideas and techniques.","PeriodicalId":394892,"journal":{"name":"2010 Annual Meeting of the North American Fuzzy Information Processing Society","volume":"24 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":"117025120","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 fuzzy approach to intensive data mining","authors":"M. Buscema, P. Sacco","doi":"10.1109/NAFIPS.2010.5548178","DOIUrl":"https://doi.org/10.1109/NAFIPS.2010.5548178","url":null,"abstract":"For many spatial processes, there is a natural need to find out the point of origin on the basis of the available scatter of observations; think for instance of finding out the home-base of a criminal given the actual distribution of crime scenes, or the outbreak source of an epidemics. We introduce a new methodology based on the notion of Topological Weighted Centroid (TWC) that allows one to draw powerful inferences also in relatively intractable cases with few observations or a poorly understood underlying data generating process. In this paper we consider reconstruction of global political and economic relationships on the basis of a small-dimensional qualitative dataset.","PeriodicalId":394892,"journal":{"name":"2010 Annual Meeting of the North American Fuzzy Information Processing Society","volume":"385 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":"122169941","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}
Soheil Davaria, Mohammad Hossein Fazel Zarandia, Burhan Turksenb
{"title":"The fuzzy reliable hub location problem","authors":"Soheil Davaria, Mohammad Hossein Fazel Zarandia, Burhan Turksenb","doi":"10.1109/NAFIPS.2010.5548271","DOIUrl":"https://doi.org/10.1109/NAFIPS.2010.5548271","url":null,"abstract":"A Hub Location Problem (HLP) deals with finding the locations of hub facilities and assignment of demand nodes to established facilities. Due to special characteristics of HLP, the overall performance of the network highly depends on proper performance of hubs. Therefore, the design of reliable networks is a critical issue to be considered. In this paper, we design a single-allocation hub-and-spoke network, so that the reliability of the network is maximized. The reliability of each arc is assumed to be a fuzzy variable. An expected value maximization version of the problem is proposed and a simulation-embedded simulated annealing is presented. Finally, a set of test problems are presented and the results are analyzed.","PeriodicalId":394892,"journal":{"name":"2010 Annual Meeting of the North American Fuzzy Information Processing Society","volume":"71 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":"114788257","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 ontologies building method: Fuzzy OntoMethodology","authors":"Hanen Ghorbel, A. Bahri, R. Bouaziz","doi":"10.1109/NAFIPS.2010.5548211","DOIUrl":"https://doi.org/10.1109/NAFIPS.2010.5548211","url":null,"abstract":"Building ontologies is very important for diverse domains and especially for semantic Web. We find in the literature many methods and tools for this building. However, the fuzzy aspect is not enough studied in these methods and tools, whereas information systems can include uncertainties and imperfections. The goal of the definition of fuzzy ontologies is to integrate these characteristics. So, we must be able to modulate uncertainties, on the one hand, and to product representations accessible and understandable by machines, on the other hand. If we find actually many building methods and editors for classic ontologies (i.e., crisp or exact), we do not find such methods for fuzzy ontologies. Then, this paper defines our work for fuzzy ontologies building. It presents our fuzzy ontologies building method “Fuzzy OntoMethodology”.","PeriodicalId":394892,"journal":{"name":"2010 Annual Meeting of the North American Fuzzy Information Processing Society","volume":"147 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":"132887080","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}