Relevant bibliographies by topics / Fuzzy logic

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Fuzzy logic'

Author: Grafiati
Published: 4 June 2021
Last updated: 25 July 2025

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Journal articles on the topic "Fuzzy logic"

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BOBILLO, FERNANDO, MIGUEL DELGADO, JUAN GÓMEZ-ROMERO, and UMBERTO STRACCIA. "JOINING GÖDEL AND ZADEH FUZZY LOGICS IN FUZZY DESCRIPTION LOGICS." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 20, no. 04 (2012): 475–508. http://dx.doi.org/10.1142/s0218488512500249.

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Ontologies have succeeded as a knowledge representation formalism in many domains of application. Nevertheless, they are not suitable to represent vague or imprecise information. To overcome this limitation, several extensions to classical ontologies based on fuzzy logic have been proposed. Even though different fuzzy logics lead to fuzzy ontologies with very different logical properties, the combined use of different fuzzy logics has received little attention to date. This paper proposes a fuzzy extension of the Description Logic [Formula: see text] — the logic behind the ontology language OW
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Metcalfe, George, and Franco Montagna. "Substructural fuzzy logics." Journal of Symbolic Logic 72, no. 3 (2007): 834–64. http://dx.doi.org/10.2178/jsl/1191333844.

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AbstractSubstructural fuzzy logics are substructural logics that are complete with respect to algebras whose lattice reduct is the real unit interval [0, 1]. In this paper, we introduce Uninorm logic UL as Multiplicative additive intuitionistic linear logic MAILL extended with the prelinearity axiom ((A → B) ∧ t) V ((B → A)∧ t). Axiomatic extensions of UL include known fuzzy logics such as Monoidal t-norm logic MIX and Gödel logic G, and new weakening-free logics. Algebraic semantics for these logics are provided by subvarieties of (representable) pointed bounded commutative residuated lattice
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Gehrke, Mai, Carol Walker, and Elbert Walker. "A Mathematical Setting for Fuzzy Logics." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 05, no. 03 (1997): 223–38. http://dx.doi.org/10.1142/s021848859700021x.

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The setup of a mathematical propositional logic is given in algebraic terms, describing exactly when two choices of truth value algebras give the same logic. The propositional logic obtained when the algebra of truth values is the real numbers in the unit interval equipped with minimum, maximum and -x=1-x for conjunction, disjunction and negation, respectively, is the standard propositional fuzzy logic. This is shown to be the same as three-valued logic. The propositional logic obtained when the algebra of truth values is the set {(a, b)|a≤ b and a,b∈[0,1]} of subintervals of the unit interval
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MIYAKOSHI, Masaaki. "Fuzzy Logic." Journal of Japan Society for Fuzzy Theory and Systems 4, no. 1 (1992): 90–97. http://dx.doi.org/10.3156/jfuzzy.4.1_90.

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Chast, Roz. "Fuzzy Logic." Scientific American 289, no. 2 (2003): 96. http://dx.doi.org/10.1038/scientificamerican0803-96.

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Chast, Roz. "Fuzzy Logic." Scientific American 288, no. 6 (2003): 92. http://dx.doi.org/10.1038/scientificamerican0603-92.

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Klir, G. J. "Fuzzy logic." IEEE Potentials 14, no. 4 (1995): 10–15. http://dx.doi.org/10.1109/45.468220.

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Chast, Roz. "Fuzzy Logic." Scientific American 288, no. 3 (2003): 112. http://dx.doi.org/10.1038/scientificamerican0303-112.

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Chast, Roz. "Fuzzy Logic." Scientific American 287, no. 6 (2002): 139. http://dx.doi.org/10.1038/scientificamerican1202-139.

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Chast, Roz. "Fuzzy Logic." Scientific American 289, no. 6 (2003): 128. http://dx.doi.org/10.1038/scientificamerican1203-128.

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Dissertations / Theses on the topic "Fuzzy logic"

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Cerami, Marco. "Fuzzy Description Logics from a Mathematical Fuzzy Logic point of view." Doctoral thesis, Universitat de Barcelona, 2012. http://hdl.handle.net/10803/113374.

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Description Logic is a formalism that is widely used in the framework of Knowledge Representation and Reasoning in Artificial Intelligence. They are based on Classical Logic in order to guarantee the correctness of the inferences on the required reasoning tasks. It is indeed a fragment of First Order Predicate Logic whose language is strictly related to the one of Modal Logic. Fuzzy Description Logic is the generalization of the classical Description Logic framework thought for reasoning with vague concepts that often arise in practical applications. Fuzzy Description Logic has been investi
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Chen, Guiming. "Fuzzy FOIL: A fuzzy logic based inductive logic programming system." Thesis, University of Ottawa (Canada), 1996. http://hdl.handle.net/10393/9621.

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In many domains, characterizations of a given attribute are imprecise, uncertain and incomplete in the available learning examples. The definitions of classes may be vague. Learning systems are frequently forced to deal with such uncertainty. Traditional learning systems are designed to work in the domains where imprecision and uncertainty in the data are absent. Those learning systems are limited because of their impossibility to cope with uncertainty--a typical feature of real-world data. In this thesis, we developed a fuzzy learning system which combines inductive learning with a fuzzy appr
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Coupland, Simon C. "Geometric fuzzy logic systems." Thesis, De Montfort University, 2006. http://hdl.handle.net/2086/10782.

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There has recently been a significant increase in academic interest in the field oftype-2 fuzzy sets and systems. Type-2 fuzzy systems offer the ability to model and reason with uncertain concepts. When faced with uncertainties type-2 fuzzy systems should, theoretically, give an increase in performance over type-l fuzzy systems. However, the computational complexity of generalised type-2 fuzzy systems is significantly higher than type-l systems. A direct consequence of this is that, prior to this thesis, generalised type-2 fuzzy logic has not yet been applied in a time critical domain, such as
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Lundqvist, Patrik, and Michael Enhörning. "Speltestning : Med Fuzzy Logic." Thesis, Högskolan i Borås, Institutionen Handels- och IT-högskolan, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:hb:diva-20260.

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Vid design av ett dataspel försöker speldesignern ofta skapa banor och fiender som tvingar spelaren att använda olika strategier för att överleva. För att hitta dessa strategier krävs speltestning. Speltestning är tidskrävande och då också dyrt. Den enklaste metoden för att spara tid är då att använda data hooks i spelet och sedan låta testpersoner spela spelet. Data samlas då in under alla spelsessioner och lagras i loggfiler.Med hjälp av data hooks samlades data in till denna rapport. Spelet som analyserades var ett spel av typen top-down-shooter. Anledning till att detta spel valdes var att
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Genito, Daniele. "Some topics in fuzzy logic." Doctoral thesis, Universita degli studi di Salerno, 2010. http://hdl.handle.net/10556/113.

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2008-2009<br>Si trattano diversi aspetti della logica fuzzy, in particolare: 1) le proprietà preservate da un modello fuzzy ogniqualvolta esso è sottoposto a qualche genere di modifica; 2) la programmazione logica fuzzy, la logica della similarità e la metaprogrammazione, considerando la relazione di sinonimia tra predicati; 3) la connessione tra logica fuzzy e teoria dei bireticoli per il trattamento sia della verità che del grado di informazione.<br>VIII n.s.
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García, Z. Yohn E. "Fuzzy logic in process control : a new fuzzy logic controller and an improved fuzzy-internal model controller." [Tampa, Fla] : University of South Florida, 2006. http://purl.fcla.edu/usf/dc/et/SFE0001552.

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García, Z. Yohn E. "Fuzzy logic in process control: A new fuzzy logic controller and an improved fuzzy-internal model controller." Scholar Commons, 2006. http://scholarcommons.usf.edu/etd/2529.

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Two fuzzy controllers are presented. A fuzzy controller with intermediate variable designed for cascade control purposes is presented as the FCIV controller. An intermediate variable and a new set of fuzzy logic rules are added to a conventional Fuzzy Logic Controller (FLC) to build the Fuzzy Controller with Intermediate Variable (FCIV). The new controller was tested in the control of a nonlinear chemical process, and its performance was compared to several other controllers. The FCIV shows the best control performance regarding stability and robustness. The new controller also has an acceptab
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Al-Khalidi, Aous Nahad. "Evaluating Quality of Ziggurat of Ur Using Fuzzy Logic Concept and Fuzzy Logic Models." The Ohio State University, 2009. http://rave.ohiolink.edu/etdc/view?acc_num=osu1244041809.

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Aranibar, Luis Alfonso Quiroga. "Learning fuzzy logic from examples." Ohio : Ohio University, 1994. http://www.ohiolink.edu/etd/view.cgi?ohiou1176495652.

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Hoyle, W. J. "Fuzzy logic, control and optimisation." Thesis, University of Canterbury. Mechanical Engineering, 1996. http://hdl.handle.net/10092/6458.

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This thesis examines the utility of fuzzy logic in the field of control engineering. A tutorial introduction to the field of fuzzy control is presented during the development of an efficient fuzzy controller. Using the controller as a starting point, a set of criteria are developed that ensure a close connection between rule base construction and control surface geometry. The properties of the controller are exploited in the design of a global controller optimiser based on a genetic algorithm, and a tutorial explaining how the optimiser may be used to effect automatic controller design is give
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Books on the topic "Fuzzy logic"

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Carter, Jenny, Francisco Chiclana, Arjab Singh Khuman, and Tianhua Chen, eds. Fuzzy Logic. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-66474-9.

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Wang, Paul P., Da Ruan, and Etienne E. Kerre, eds. Fuzzy Logic. Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-71258-9.

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Lowen, R., and M. Roubens, eds. Fuzzy Logic. Springer Netherlands, 1993. http://dx.doi.org/10.1007/978-94-011-2014-2.

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Trillas, Enric, and Luka Eciolaza. Fuzzy Logic. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-14203-6.

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Bothe, Hans-Heinrich. Fuzzy Logic. Springer Berlin Heidelberg, 1993. http://dx.doi.org/10.1007/978-3-662-21929-4.

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Gerla, Giangiacomo. Fuzzy Logic. Springer Netherlands, 2001. http://dx.doi.org/10.1007/978-94-015-9660-2.

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Bothe, Hans-Heinrich. Fuzzy Logic. Springer Berlin Heidelberg, 1995. http://dx.doi.org/10.1007/978-3-662-07357-5.

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Reusch, Bernd, ed. Fuzzy Logic. Springer Berlin Heidelberg, 1993. http://dx.doi.org/10.1007/978-3-642-78694-5.

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Patyra, M. J., and D. M. Mlynek, eds. Fuzzy Logic. Vieweg+Teubner Verlag, 1996. http://dx.doi.org/10.1007/978-3-322-88955-3.

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Reusch, Bernd, ed. Fuzzy Logic. Springer Berlin Heidelberg, 1993. http://dx.doi.org/10.1007/978-3-642-78023-3.

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Book chapters on the topic "Fuzzy logic"

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El Alaoui, Mohamed. "Fuzzy Logic." In Fuzzy TOPSIS. CRC Press, 2021. http://dx.doi.org/10.1201/9781003168416-3-3.

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Gerla, Giangiacomo. "Truth-Functional Logic and Fuzzy Logic." In Fuzzy Logic. Springer Netherlands, 2001. http://dx.doi.org/10.1007/978-94-015-9660-2_8.

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Bandemer, Hans. "Fuzzy Analysis of Fuzzy Data." In Fuzzy Logic. Springer Netherlands, 1993. http://dx.doi.org/10.1007/978-94-011-2014-2_36.

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Buckley, James J., and Esfandiar Eslami. "Logic." In An Introduction to Fuzzy Logic and Fuzzy Sets. Physica-Verlag HD, 2002. http://dx.doi.org/10.1007/978-3-7908-1799-7_2.

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Trillas, Enric, and Luka Eciolaza. "Fuzzy Relations." In Fuzzy Logic. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-14203-6_4.

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Trillas, Enric, and Luka Eciolaza. "Fuzzy Arithmetic." In Fuzzy Logic. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-14203-6_6.

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Trillas, Enric, and Luka Eciolaza. "Fuzzy Measures." In Fuzzy Logic. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-14203-6_7.

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Voigt, Michael, and Horst J. Bessai. "Fuzzy Equalization." In Fuzzy Logic. Springer Berlin Heidelberg, 1993. http://dx.doi.org/10.1007/978-3-642-78694-5_7.

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Bothe, Hans-Heinrich. "Fuzzy-Regelung." In Fuzzy Logic. Springer Berlin Heidelberg, 1993. http://dx.doi.org/10.1007/978-3-662-21929-4_8.

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Bothe, Hans-Heinrich. "Fuzzy-Regelung." In Fuzzy Logic. Springer Berlin Heidelberg, 1995. http://dx.doi.org/10.1007/978-3-662-07357-5_8.

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Conference papers on the topic "Fuzzy logic"

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Chen, Xinjia, and Paul Muench. "Deviation of fuzzy logic from earthling logic." In Unmanned Systems Technology XXVII, edited by Paul L. Muench, Robert Diltz, and Raja Suresh. SPIE, 2025. https://doi.org/10.1117/12.3052884.

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Guest, Clark C. "Optical fuzzy logic processor." In OSA Annual Meeting. Optica Publishing Group, 1992. http://dx.doi.org/10.1364/oam.1992.fdd7.

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Fuzzy logic provides a means of working with qualitative data and rules. Like neural networks, fuzzy logic provides a mapping from a space of input variables to a space of output variables. Unlike neural networks, fuzzy logic provides a direct means of incorporating human expertise. For a given problem, the computational requirements for a fuzzy logic solution are often significantly less than those required by a neural network solution. However, fuzzy logic implementations are faced with a need for global communication in the distribution and collection of data. An optical processing architec
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Zhao, Jidi, and Harold Boley. "Combining Fuzzy Description Logics and Fuzzy Logic Programs." In 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology. IEEE, 2008. http://dx.doi.org/10.1109/wiiat.2008.363.

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Cerami, Marco, Angel Garcia-Cerdana, and Francesc Esteva. "From classical Description Logic to n-graded Fuzzy Description Logic." In 2010 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, 2010. http://dx.doi.org/10.1109/fuzzy.2010.5584114.

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Das, Abhijit, Umapada Pal, Miguel Angel Ferrer Ballester, and Michael Blumenstein. "Fuzzy logic based selera recognition." In 2014 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, 2014. http://dx.doi.org/10.1109/fuzz-ieee.2014.6891684.

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Burda, Michal. "Linguistic fuzzy logic in R." In 2015 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, 2015. http://dx.doi.org/10.1109/fuzz-ieee.2015.7337826.

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Greenfield, Sarah, Francisco Chiclana, and Scott Dick. "Interval-valued complex fuzzy logic." In 2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, 2016. http://dx.doi.org/10.1109/fuzz-ieee.2016.7737939.

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Konstantopoulos, Stasinos, and Angelos Charalambidis. "Formulating description logic learning as an Inductive Logic Programming task." In 2010 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, 2010. http://dx.doi.org/10.1109/fuzzy.2010.5584417.

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Gorman, Kevin J., and Kourosh J. Rahnamai. "Rapid Prototyping of Fuzzy Logic Controllers." In ASME 1996 Design Engineering Technical Conferences and Computers in Engineering Conference. American Society of Mechanical Engineers, 1996. http://dx.doi.org/10.1115/96-detc/cie-1450.

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Abstract The rapid prototyping of fuzzy logic controllers is accomplished by using the tools Matlab, Simulink, Fuzzy Logic Toolkit, and Real-Time Workshop. Device drivers were developed for Simulink for interfacing with DT2801 and DT2821 data acquisition boards. The fuzzy logic inference engine for the Fuzzy Logic Toolkit was modified to allow the systems to work as independent programs and to be downloadable to DSP (Digital Signal Processing) boards. Simulink is used to graphically implement fuzzy logic controllers. The Real-Time Workshop is used to compile blocks from Simulink into C code, t
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Esteva, Francese, Lluis Godo, and Ricardo Oscar Rodriguez. "On the relation between modal and multi-modal logics over Łukasiewicz logic." In 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, 2017. http://dx.doi.org/10.1109/fuzz-ieee.2017.8015703.

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Reports on the topic "Fuzzy logic"

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Tailor, Sanjay. Fuzzy Logic. Defense Technical Information Center, 1996. http://dx.doi.org/10.21236/ada310470.

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Meitzler, Thomas J., David Bednarz, E. J. Sohn, Kimberly Lane, and Darryl Bryk. Fuzzy Logic Based Image Fusion. Defense Technical Information Center, 2002. http://dx.doi.org/10.21236/ada405123.

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Combs, James E. Advanced Control Techniques with Fuzzy Logic. Defense Technical Information Center, 2014. http://dx.doi.org/10.21236/ada604019.

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Borgwardt, Stefan, Felix Distel, and Rafael Peñaloza. Gödel Description Logics: Decidability in the Absence of the Finitely-Valued Model Property. Technische Universität Dresden, 2013. http://dx.doi.org/10.25368/2022.199.

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In the last few years there has been a large effort for analysing the computational properties of reasoning in fuzzy Description Logics. This has led to a number of papers studying the complexity of these logics, depending on their chosen semantics. Surprisingly, despite being arguably the simplest form of fuzzy semantics, not much is known about the complexity of reasoning in fuzzy DLs w.r.t. witnessed models over the Gödel t-norm. We show that in the logic G-IALC, reasoning cannot be restricted to finitely valued models in general. Despite this negative result, we also show that all the stan
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Bharadwaj, Arjun, and Jerry M. Mendel. Fuzzy Logic for Unattended Ground Sensor Fusion. Defense Technical Information Center, 2006. http://dx.doi.org/10.21236/ada444339.

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Almufti, Ali. Parallel Hybrid Vehicles using Fuzzy Logic Control. Defense Technical Information Center, 2009. http://dx.doi.org/10.21236/ada513229.

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Borgwardt, Stefan, Marco Cerami, and Rafael Peñaloza. Subsumption in Finitely Valued Fuzzy EL. Technische Universität Dresden, 2015. http://dx.doi.org/10.25368/2022.212.

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Aus der Einleitung: Description Logics (DLs) are a family of knowledge representation formalisms that are successfully applied in many application domains. They provide the logical foundation for the Direct Semantics of the standard web ontology language OWL2. The light-weight DL EL, underlying the OWL2 EL profile, is of particular interest since all common reasoning problems are polynomial in this logic, and it is used in many prominent biomedical ontologies like SNOMEDCT and the Gene Ontology.
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Borgwardt, Stefan, and Rafael Peñaloza. Undecidability of Fuzzy Description Logics. Technische Universität Dresden, 2011. http://dx.doi.org/10.25368/2022.184.

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Fuzzy description logics (DLs) have been investigated for over two decades, due to their capacity to formalize and reason with imprecise concepts. Very recently, it has been shown that for several fuzzy DLs, reasoning becomes undecidable. Although the proofs of these results differ in the details of each specific logic considered, they are all based on the same basic idea. In this report, we formalize this idea and provide sufficient conditions for proving undecidability of a fuzzy DL. We demonstrate the effectiveness of our approach by strengthening all previously-known undecidability results
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Liang, Qilian. Energy Efficient Wireless Sensor Networks Using Fuzzy Logic. Defense Technical Information Center, 2005. http://dx.doi.org/10.21236/ada434605.

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Liang, Qilian. Energy Efficient Wireless Sensor Networks Using Fuzzy Logic. Defense Technical Information Center, 2003. http://dx.doi.org/10.21236/ada419061.

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