Letteratura scientifica selezionata sul tema "Fuzzy"
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Articoli di riviste sul tema "Fuzzy"
Şengönül, M., e Z. Zararsız. "Some Additions to the Fuzzy Convergent and Fuzzy Bounded Sequence Spaces of Fuzzy Numbers". Abstract and Applied Analysis 2011 (2011): 1–12. http://dx.doi.org/10.1155/2011/837584.
Testo completoZhang, Xiaohong. "On Some Fuzzy Filters in Pseudo-BCIAlgebras". Scientific World Journal 2014 (2014): 1–8. http://dx.doi.org/10.1155/2014/718972.
Testo completoMukherjee, M. N., e S. P. Sinha. "Fuzzyθ-closure operator on fuzzy topological spaces". International Journal of Mathematics and Mathematical Sciences 14, n. 2 (1991): 309–14. http://dx.doi.org/10.1155/s0161171291000364.
Testo completoKumbhojkar, H. V. "Proper Fuzzification of Prime Ideals of a Hemiring". Advances in Fuzzy Systems 2012 (2012): 1–8. http://dx.doi.org/10.1155/2012/801650.
Testo completoUehara, Kiyohiko, e Kaoru Hirota. "A Fast Method for Fuzzy Rules Learning with Derivative-Free Optimization by Formulating Independent Evaluations of Each Fuzzy Rule". Journal of Advanced Computational Intelligence and Intelligent Informatics 25, n. 2 (20 marzo 2021): 213–25. http://dx.doi.org/10.20965/jaciii.2021.p0213.
Testo completoLee, Seok Jong, e Eun Pyo Lee. "Fuzzyr-continuous and fuzzyr-semicontinuous maps". International Journal of Mathematics and Mathematical Sciences 27, n. 1 (2001): 53–63. http://dx.doi.org/10.1155/s0161171201010882.
Testo completoJeon, Joung Kon, Young Bae Jun e Jin Han Park. "Intuitionistic fuzzy alpha-continuity and intuitionistic fuzzy precontinuity". International Journal of Mathematics and Mathematical Sciences 2005, n. 19 (2005): 3091–101. http://dx.doi.org/10.1155/ijmms.2005.3091.
Testo completoRaj, A. Stanley, D. Hudson Oliver e Y. Srinivas. "Geoelectrical Data Inversion by Clustering Techniques of Fuzzy Logic to Estimate the Subsurface Layer Model". International Journal of Geophysics 2015 (2015): 1–11. http://dx.doi.org/10.1155/2015/134834.
Testo completoMa, Zhen Ming. "Some Types of Generalized Fuzzyn-Fold Filters in Residuated Lattices". Abstract and Applied Analysis 2013 (2013): 1–8. http://dx.doi.org/10.1155/2013/736872.
Testo completoRenuka, R., e V. Seenivasan. "On Intuitionistic Fuzzyβ-Almost Compactness andβ-Nearly Compactness". Scientific World Journal 2015 (2015): 1–5. http://dx.doi.org/10.1155/2015/869740.
Testo completoTesi sul tema "Fuzzy"
Mezzomo, Ivan. "On fuzzy ideals and fuzzy filters of fuzzy lattices". Universidade Federal do Rio Grande do Norte, 2013. http://repositorio.ufrn.br:8080/jspui/handle/123456789/18692.
Testo completoIn the literature there are several proposals of fuzzi cation of lattices and ideals concepts. Chon in (Korean J. Math 17 (2009), No. 4, 361-374), using the notion of fuzzy order relation de ned by Zadeh, introduced a new notion of fuzzy lattice and studied the level sets of fuzzy lattices, but did not de ne a notion of fuzzy ideals for this type of fuzzy lattice. In this thesis, using the fuzzy lattices de ned by Chon, we de ne fuzzy homomorphism between fuzzy lattices, the operations of product, collapsed sum, lifting, opposite, interval and intuitionistic on bounded fuzzy lattices. They are conceived as extensions of their analogous operations on the classical theory by using this de nition of fuzzy lattices and introduce new results from these operators. In addition, we de ne ideals and lters of fuzzy lattices and concepts in the same way as in their characterization in terms of level and support sets. One of the results found here is the connection among ideals, supports and level sets. The reader will also nd the de nition of some kinds of ideals and lters as well as some results with respect to the intersection among their families. Moreover, we introduce a new notion of fuzzy ideals and fuzzy lters for fuzzy lattices de ned by Chon. We de ne types of fuzzy ideals and fuzzy lters that generalize usual types of ideals and lters of lattices, such as principal ideals, proper ideals, prime ideals and maximal ideals. The main idea is verifying that analogous properties in the classical theory on lattices are maintained in this new theory of fuzzy ideals. We also de ne, a fuzzy homomorphism h from fuzzy lattices L and M and prove some results involving fuzzy homomorphism and fuzzy ideals as if h is a fuzzy monomorphism and the fuzzy image of a fuzzy set ~h(I) is a fuzzy ideal, then I is a fuzzy ideal. Similarly, we prove for proper, prime and maximal fuzzy ideals. Finally, we prove that h is a fuzzy homomorphism from fuzzy lattices L into M if the inverse image of all principal fuzzy ideals of M is a fuzzy ideal of L. Lastly, we introduce the notion of -ideals and - lters of fuzzy lattices and characterize it by using its support and its level set. Moreover, we prove some similar properties in the classical theory of - ideals and - lters, such as, the class of -ideals and - lters are closed under intersection. We also de ne fuzzy -ideals of fuzzy lattices, some properties analogous to the classical theory are also proved and characterize a fuzzy -ideal on operation of product between bounded fuzzy lattices L and M and prove some results.
Biba, Vladislav. "Generované fuzzy implikátory ve fuzzy rozhodování". Doctoral thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2012. http://www.nusl.cz/ntk/nusl-233558.
Testo completoCosta, Claudilene Gomes da. "Probabilidades imprecisas: intervalar, fuzzy e fuzzy intuicionista". Universidade Federal do Rio Grande do Norte, 2012. http://repositorio.ufrn.br:8080/jspui/handle/123456789/15202.
Testo completoThe idea of considering imprecision in probabilities is old, beginning with the Booles George work, who in 1854 wanted to reconcile the classical logic, which allows the modeling of complete ignorance, with probabilities. In 1921, John Maynard Keynes in his book made explicit use of intervals to represent the imprecision in probabilities. But only from the work ofWalley in 1991 that were established principles that should be respected by a probability theory that deals with inaccuracies. With the emergence of the theory of fuzzy sets by Lotfi Zadeh in 1965, there is another way of dealing with uncertainty and imprecision of concepts. Quickly, they began to propose several ways to consider the ideas of Zadeh in probabilities, to deal with inaccuracies, either in the events associated with the probabilities or in the values of probabilities. In particular, James Buckley, from 2003 begins to develop a probability theory in which the fuzzy values of the probabilities are fuzzy numbers. This fuzzy probability, follows analogous principles to Walley imprecise probabilities. On the other hand, the uses of real numbers between 0 and 1 as truth degrees, as originally proposed by Zadeh, has the drawback to use very precise values for dealing with uncertainties (as one can distinguish a fairly element satisfies a property with a 0.423 level of something that meets with grade 0.424?). This motivated the development of several extensions of fuzzy set theory which includes some kind of inaccuracy. This work consider the Krassimir Atanassov extension proposed in 1983, which add an extra degree of uncertainty to model the moment of hesitation to assign the membership degree, and therefore a value indicate the degree to which the object belongs to the set while the other, the degree to which it not belongs to the set. In the Zadeh fuzzy set theory, this non membership degree is, by default, the complement of the membership degree. Thus, in this approach the non-membership degree is somehow independent of the membership degree, and this difference between the non-membership degree and the complement of the membership degree reveals the hesitation at the moment to assign a membership degree. This new extension today is called of Atanassov s intuitionistic fuzzy sets theory. It is worth noting that the term intuitionistic here has no relation to the term intuitionistic as known in the context of intuitionistic logic. In this work, will be developed two proposals for interval probability: the restricted interval probability and the unrestricted interval probability, are also introduced two notions of fuzzy probability: the constrained fuzzy probability and the unconstrained fuzzy probability and will eventually be introduced two notions of intuitionistic fuzzy probability: the restricted intuitionistic fuzzy probability and the unrestricted intuitionistic fuzzy probability
A id?ia de considerar imprecis?o em probabilidades ? antiga, remontando aos trabalhos de George Booles, que em 1854 pretendia conciliar a l?gica cl?ssica, que permite modelar ignor?ncia completa, com probabilidades. Em 1921, John Maynard Keynes em seu livro fez uso expl?cito de intervalos para representar a imprecis?o nas probabilidades. Por?m, apenas a partir dos trabalhos de Walley em 1991 que foram estabelecidos princ?pios que deveriam ser respeitados por uma teoria de probabilidades que lide com imprecis?es. Com o surgimento da teoria dos conjuntos fuzzy em 1965 por Lotfi Zadeh, surge uma outra forma de lidar com incertezas e imprecis?es de conceitos. Rapidamente, come?aram a se propor diversas formas de considerar as id?ias de Zadeh em probabilidades, para lidar com imprecis?es, seja nos eventos associados ?s probabilidades como aos valores das probabilidades. Em particular, James Buckley, a partir de 2003 come?a a desenvolver uma teoria de probabilidade fuzzy em que os valores das probabilidades sejam n?meros fuzzy. Esta probabilidade fuzzy segue princ?pios an?logos ao das probabilidades imprecisas de Walley. Por outro lado, usar como graus de verdade n?meros reais entre 0 e 1, como proposto originalmente por Zadeh, tem o inconveniente de usar valores muito precisos para lidar com incertezas (como algu?m pode diferenciar de forma justa que um elemento satisfaz uma propriedade com um grau 0.423 de algo que satisfaz com grau 0.424?). Isto motivou o surgimento de diversas extens?es da teoria dos conjuntos fuzzy pelo fato de incorporar algum tipo de imprecis?o. Neste trabalho ? considerada a extens?o proposta por Krassimir Atanassov em 1983, que adicionou um grau extra de incerteza para modelar a hesita??o ao momento de se atribuir o grau de pertin?ncia, e portanto, um valor indicaria o grau com o qual o objeto pertence ao conjunto, enquanto o outro, o grau com o qual n?o pertence. Na teoria dos conjuntos fuzzy de Zadeh, esse grau de n?o-pertin?ncia por defeito ? o complemento do grau de pertin?ncia. Assim, nessa abordagem o grau de n?o-pertin?ncia ? de alguma forma independente do grau de pertin?ncia, e nessa diferencia entre essa n?o-pertin?ncia e o complemento do grau de pertin?ncia revela a hesita??o presente ao momento de se atribuir o grau de pertin?ncia. Esta nova extens?o hoje em dia ? chamada de teoria dos conjuntos fuzzy intuicionistas de Atanassov. Vale salientar, que o termo intuicionista aqui n?o tem rela??o com o termo intuicionista como conhecido no contexto de l?gica intuicionista. Neste trabalho ser? desenvolvida duas propostas de probabilidade intervalar: a probabilidade intervalar restrita e a probabilidade intervalar irrestrita; tamb?m ser?o introduzidas duas no??es de probabilidade fuzzy: a probabilidade fuzzy restrita e a probabilidade fuzzy irrestrita e por fim ser?o introduzidas duas no??es de probabilidade fuzzy intuicionista: a probabilidade fuzzy intuicionista restrita e a probabilidade fuzzy intuicionista irrestrita
Klapil, Ondřej. "Fuzzy systémy s netradičními antecedenty fuzzy pravidel". Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2016. http://www.nusl.cz/ntk/nusl-220884.
Testo completoGomes, Luciana Takata 1984. "On fuzzy differential equations = Sobre equações diferenciais fuzzy". [s.n.], 2014. http://repositorio.unicamp.br/jspui/handle/REPOSIP/307565.
Testo completoTese (doutorado) - Universidade Estadual de Campinas, Instituto de Matemática, Estatística e Computação Científica
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Resumo: A partir da proposta das definições de derivada e integral fuzzy via extensão de Zadeh dos respectivos operadores para funções clássicas, obtemos uma versão do teorema fundamental do cálculo e desenvolvemos uma nova teoria de equações diferenciais fuzzy (EDFs). Diferentemente dos conceitos anteriores de derivadas (Hukuhara e generalizadas) e integrais para funções fuzzy, em que as funções assumem valores em conjuntos fuzzy, a abordagem aqui proposta lida com tubos fuzzy de funções (subconjuntos fuzzy de espaços de funções). Sob condições razoáveis, as novas operações equivalem a diferenciar (ou integrar) as funções clássicas dos níveis. Apresentamos as abordagens anteriores de EDFs mais conhecidas e, para realizar comparações com a nova teoria, calculamos os conjuntos atingíveis fuzzy das soluções. Provamos que algumas soluções da teoria proposta equivalem às via derivada fortemente generalizada. Também demonstramos a equivalência, sob determinadas condições, com as soluções via inclusões diferenciais fuzzy e extensão de Zadeh da solução clássica. Apesar destas duas abordagens não tratarem de EDFs, elas são largamente difundidas por utilizarem derivadas de funções clássicas (de modo similar ao aqui proposto) e de preservarem características das soluções de sistemas dinâmicos clássicos. Esses são fatos vantajosos, pois mostram que a teoria proposta, além de tratar de EDFs, possui propriedades desejáveis das outras duas mencionadas, permitindo a ocorrência de estabilidade e periodicidade de soluções, por exemplo. A teoria é ilustrada através de sua aplicação em modelos biológicos e análise dos resultados
Abstract: From the definition of fuzzy derivative and integral via Zadeh's extension of the derivative and integral for classical functions we obtain a fundamental theorem of calculus and develop a new theory for fuzzy differential equations (FDEs). Different from the previous concepts of fuzzy derivatives (Hukuhara and generalized derivatives) and integrals, defined for fuzzy-set-valued functions, the approach we propose deals with fuzzy bunches of functions (fuzzy subsets of spaces of functions). Under reasonable conditions, the new operations are equivalent to differentiating (or integrating) the classical functions of the levels. We present the most known previous approaches of FDEs. Comparisons with the new theory we propose are carried out calculating fuzzy attainable sets of the solutions. Under certain conditions, the solutions via strongly generalized derivative coincide with solutions using our approach. The same happens with solutions to fuzzy differential inclusions and Zadeh's extension of the crisp solution. Although these two methods do not treat FDEs, they are widespread for making use of classical functions (similarly to what is proposed in this thesis) and for preserving properties of classical dynamical systems. These are advantageous features since it shows that the new theory presents desirable properties of the other two mentioned theories (allowing for instance periodicity and stability of solutions), besides treating FDEs. The theory is illustrated by applying it on biological models and commenting the results
Doutorado
Matematica Aplicada
Doutora em Matemática Aplicada
Naman, Saleem Muhammad. "Eigen Fuzzy Sets of Fuzzy Relation with Applications". Thesis, Blekinge Tekniska Högskola, Sektionen för ingenjörsvetenskap, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-4060.
Testo completoLee, John Wan Tung. "The discovery of fuzzy rules from fuzzy databases". Thesis, University of Sunderland, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.298322.
Testo completoHüsselmann, Claus. "Fuzzy-Geschäftsprozessmanagement /". Lohmar ; Köln : Eul, 2003. http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&doc_number=010483351&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA.
Testo completoStrobel, Cornelia. "Fuzzy Fingerprinting". Universitätsbibliothek Chemnitz, 2005. http://nbn-resolving.de/urn:nbn:de:swb:ch1-200500106.
Testo completoFingerabdrücke besitzen sowohl in der Kryptographie als auch in der Biometrie eine große Bedeutung. In kryptographischen Anwendungen werden diese durch Einweg-Hash-Verfahren erzeugt, die für bestimmte Anwendungen auch kollisionsresitent sein müssen. In der Praxis schenken Benutzer diesen Fingerprints weit weniger Aufmerksamkeit - oft genügt es nur hinreichend ähnliche Fingerprints auszugeben, um die Nutzer zu täuschen Die Kriterien, die dabei erfüllt sein müssen und die Erzeugung dieser "Fuzzy Fingerprints" sind Hauptbestandteil dieses Vortrags. Durch die Demonstration eines Tools im praktischen Einsatz wird dieser abgeschlossen
Murugan, Anand. "Fuzzy blackholes". Pomona College, 2007. http://ccdl.libraries.claremont.edu/u?/stc,18.
Testo completoLibri sul tema "Fuzzy"
Boynton, Sandra. Fuzzy, fuzzy, fuzzy!: Touch, skritch, & tickle book. New York, NY: Little Simon, 2003.
Cerca il testo completoSiegfried, Gottwald, a cura di. Fuzzy sets, fuzzy logic, fuzzy methods with applications. Chichester: J. Wiley, 1995.
Cerca il testo completoAngleberger, Tom. Fuzzy. New York: Abrams, 2016.
Cerca il testo completoKahlert, Jörg, e Hubert Frank. Fuzzy-Logik und Fuzzy-Control. Wiesbaden: Vieweg+Teubner Verlag, 1994. http://dx.doi.org/10.1007/978-3-322-89197-6.
Testo completoKahlert, Jörg, e Hubert Frank. Fuzzy-Logik und Fuzzy-Control. Wiesbaden: Vieweg+Teubner Verlag, 1993. http://dx.doi.org/10.1007/978-3-322-83760-8.
Testo completoGottwald, Siegfried. Fuzzy Sets and Fuzzy Logic. Wiesbaden: Vieweg+Teubner Verlag, 1993. http://dx.doi.org/10.1007/978-3-322-86812-1.
Testo completoDriankov, Dimiter, Peter W. Eklund e Anca L. Ralescu, a cura di. Fuzzy Logic and Fuzzy Control. Berlin, Heidelberg: Springer Berlin Heidelberg, 1994. http://dx.doi.org/10.1007/3-540-58279-7.
Testo completoMordeson, John N., e Premchand S. Nair, a cura di. Fuzzy Graphs and Fuzzy Hypergraphs. Heidelberg: Physica-Verlag HD, 2000. http://dx.doi.org/10.1007/978-3-7908-1854-3.
Testo completoMaria, Bojadziev, a cura di. Fuzzy sets, fuzzy logic, applications. Singapore: World Scientific Pub. Co., 1995.
Cerca il testo completo1932-, Klir George J., e Yuan Bo, a cura di. Fuzzy sets, fuzzy logic, and fuzzy systems: Selected papers. Singapore: World Scientific, 1996.
Cerca il testo completoCapitoli di libri sul tema "Fuzzy"
Rommelfanger, Heinrich. "Fuzzy-Wahrscheinlichkeiten, Fuzzy-Alternativen, Fuzzy-Zustände". In Fuzzy Decision Support-Systeme, 120–29. Berlin, Heidelberg: Springer Berlin Heidelberg, 1994. http://dx.doi.org/10.1007/978-3-642-57929-5_5.
Testo completoRommelfanger, Heinrich. "Fuzzy-Wahrscheinlichkeiten, Fuzzy-Alternativen, Fuzzy-Zustände". In Entscheiden bei Unschärfe, 126–38. Berlin, Heidelberg: Springer Berlin Heidelberg, 1988. http://dx.doi.org/10.1007/978-3-642-97118-1_4.
Testo completoNowé, Ann. "Keep Fuzzy Controllers Fuzzy". In International Series in Intelligent Technologies, 267–89. Boston, MA: Springer US, 1995. http://dx.doi.org/10.1007/978-1-4615-2357-4_11.
Testo completoMann, Heinz, Horst Schiffelgen, Rainer Froriep e Klaus Webers. "Fuzzy-Regler (Fuzzy-Controller)". In Einführung in die Regelungstechnik, 315–39. München: Carl Hanser Verlag GmbH & Co. KG, 2018. http://dx.doi.org/10.3139/9783446456945.010.
Testo completoPotton, Alois. "Fuzzy". In Abgründe der Informatik, 11–13. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-22975-6_3.
Testo completoBandemer, Hans. "Fuzzy Analysis of Fuzzy Data". In Fuzzy Logic, 385–94. Dordrecht: Springer Netherlands, 1993. http://dx.doi.org/10.1007/978-94-011-2014-2_36.
Testo completoKahlert, Jörg, e Hubert Frank. "Fuzzy-Set-Theorie". In Fuzzy-Logik und Fuzzy-Control, 5–39. Wiesbaden: Vieweg+Teubner Verlag, 1994. http://dx.doi.org/10.1007/978-3-322-89197-6_1.
Testo completoKahlert, Jörg, e Hubert Frank. "Fuzzy-PID-Reglerentwurf". In Fuzzy-Logik und Fuzzy-Control, 311–22. Wiesbaden: Vieweg+Teubner Verlag, 1994. http://dx.doi.org/10.1007/978-3-322-89197-6_10.
Testo completoKahlert, Jörg, e Hubert Frank. "Fuzzy Construction Unit — Demo". In Fuzzy-Logik und Fuzzy-Control, 323–33. Wiesbaden: Vieweg+Teubner Verlag, 1994. http://dx.doi.org/10.1007/978-3-322-89197-6_11.
Testo completoKahlert, Jörg, e Hubert Frank. "Fuzzy-lnferenz". In Fuzzy-Logik und Fuzzy-Control, 41–82. Wiesbaden: Vieweg+Teubner Verlag, 1994. http://dx.doi.org/10.1007/978-3-322-89197-6_2.
Testo completoAtti di convegni sul tema "Fuzzy"
Qu, Yanpeng, Jiaxing Wu, Zhanwen Wu e Longzhi Yang. "Fuzzy Rule Interpolation with A General Representation of Fuzzy Sets". In 2024 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 1–8. IEEE, 2024. http://dx.doi.org/10.1109/fuzz-ieee60900.2024.10612091.
Testo completoChakeri, Alireza, Nasser Sadati e Setareh Sharifian. "Fuzzy Nash equilibrium in fuzzy games using ranking fuzzy numbers". In 2010 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, 2010. http://dx.doi.org/10.1109/fuzzy.2010.5584733.
Testo completoTorra, Vicenc, Laya Aliahmadipour e Anders Dahlbom. "Fuzzy, I-fuzzy, and H-fuzzy partitions to describe clusters". In 2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, 2016. http://dx.doi.org/10.1109/fuzz-ieee.2016.7737731.
Testo completoMezzomo, Ivan, Benjamin C. Bedregal e Regivan H. N. Santiago. "On fuzzy ideals of fuzzy lattice". In 2012 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, 2012. http://dx.doi.org/10.1109/fuzz-ieee.2012.6251307.
Testo completoGegeny, David, e Szilveszter Kovacs. "Fuzzy Interpolation of Fuzzy Rough Sets". In 2022 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, 2022. http://dx.doi.org/10.1109/fuzz-ieee55066.2022.9882837.
Testo completoRazak, Tajul Rosli, Nor Hanimah Kamis, Nurul Hanan Anuar, Jonathan M. Garibaldi e Christian Wagner. "Decomposing Conventional Fuzzy Logic Systems to Hierarchical Fuzzy Systems". In 2023 IEEE International Conference on Fuzzy Systems (FUZZ). IEEE, 2023. http://dx.doi.org/10.1109/fuzz52849.2023.10309727.
Testo completoSeki, Hirosato, e Masaharu Mizumoto. "Fuzzy singleton-type SIC fuzzy inference model". In 2013 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, 2013. http://dx.doi.org/10.1109/fuzz-ieee.2013.6622583.
Testo completoMekki, Ahmed O., Feng Lin, Hao Ying e Michael J. Simoff. "Fuzzy detectabilities for fuzzy discrete event systems". In 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, 2017. http://dx.doi.org/10.1109/fuzz-ieee.2017.8015431.
Testo completoPivert, Olivier, Olfa Slama e Virginie Thion. "Fuzzy quantified queries to fuzzy RDF databases". In 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, 2017. http://dx.doi.org/10.1109/fuzz-ieee.2017.8015632.
Testo completoKlement, Erich Peter, Radko Mesiar e Andrea Stupnanova. "Picture fuzzy sets and 3-fuzzy sets". In 2018 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, 2018. http://dx.doi.org/10.1109/fuzz-ieee.2018.8491520.
Testo completoRapporti di organizzazioni sul tema "Fuzzy"
Çitil, Hülya. Solutions of Fuzzy Differential Equation with Fuzzy Number Coefficient by Fuzzy Laplace Transform. "Prof. Marin Drinov" Publishing House of Bulgarian Academy of Sciences, settembre 2020. http://dx.doi.org/10.7546/crabs.2020.09.01.
Testo completoTailor, Sanjay. Fuzzy Logic. Fort Belvoir, VA: Defense Technical Information Center, maggio 1996. http://dx.doi.org/10.21236/ada310470.
Testo completoKersten, Paul R. Fuzzy Order Statistics and Their Application to Fuzzy Clustering. Fort Belvoir, VA: Defense Technical Information Center, agosto 1999. http://dx.doi.org/10.21236/ada368624.
Testo completoOsipov, G. S. Fuzzy elective selection model. Редакция журнала «ОПиПМ», 2019. http://dx.doi.org/10.18411/oppm-2019-26-1.
Testo completod'Haultfoeuille, Xavier, e Clément de Chaisemartin. Fuzzy differences-in-differences. Cemmap, ottobre 2015. http://dx.doi.org/10.1920/wp.cem.2015.6915.
Testo completoAtanasso, Krassimir. Elliptic Intuitionistic Fuzzy Sets. "Prof. Marin Drinov" Publishing House of Bulgarian Academy of Sciences, giugno 2021. http://dx.doi.org/10.7546/crabs.2021.06.02.
Testo completoKersten, P. R. Fuzzy Robust Statistics for Application to the Fuzzy c-Means Clustering Algorithm. Fort Belvoir, VA: Defense Technical Information Center, dicembre 1993. http://dx.doi.org/10.21236/ada274719.
Testo completoMeitzler, Thomas J., David Bednarz, E. J. Sohn, Kimberly Lane e Darryl Bryk. Fuzzy Logic Based Image Fusion. Fort Belvoir, VA: Defense Technical Information Center, luglio 2002. http://dx.doi.org/10.21236/ada405123.
Testo completoSirainen, T. IMAP4 Extension for Fuzzy Search. RFC Editor, marzo 2011. http://dx.doi.org/10.17487/rfc6203.
Testo completoKersten, P. R., e S. C. Nardone. Concepts of Fuzzy Model Assessment. Fort Belvoir, VA: Defense Technical Information Center, marzo 1994. http://dx.doi.org/10.21236/ada280641.
Testo completo