List of all publications

Monographs:

[1] R. Bělohlávek, Fuzzy Relational Systems: Foundations and Principles. Kluwer Academic/Plenum Press, New York, 2002.

[2] J. Močkoř, Groups of Divisibility. Reidel Publishing Company, London, Boston, New York, 1983.

[3] J. Močkoř, J. Alajbegovic, Approximation Theorems in Commutative Algebra. Kluwer Academic Publishers, Boston, Dordrecht, 1992.

[4] V. Novák, Fuzzy Approach to Reasoning and Decision–Making. Kluwer, Dordrecht, 1992.

[5] V. Novák, Fuzzy množiny a jejich aplikace. SNTL, Praha, 1986.

[6] V. Novák, Fuzzy množiny a jejich aplikace. SNTL, Praha, 1990.

[7] V. Novák, Fuzzy Sets and Their Applications. Adam Hilger, Bristol, 1989.

[8] V. Novák, The Alternative Mathematical Model of Linguistic Semantics and Pragmatics. Plenum Press, New York, 1992.

[9] V. Novák, Základy fuzzy modelování. BEN-technická literatura, Praha, 2000.

[10] V. Novák, I. Perfilieva, Discovering the World with Fuzzy Logic. Springer-Verlag, Heidelberg, 2000.

[11] V. Novák, I. Perfilieva, J. Močkoř, Matematiceskije principy necetkoj logiki. Fizmatlit Nauka, Moskva, 2006.

[12] V. Novák, I. Perfilieva, J. Močkoř, Mathematical Principles of Fuzzy Logic. Kluwer Academic publishers, Boston/Dordrecht{London, 1999.

[13] I. Perfilieva, Applications of the Fuzzy Set Theory. VINITI, Moskva, Rusko, 1990.

[14] I. Perfiljeva, T. Afanasieva, N. Yarushkina, Intellectualjnyj Analiz Vremennyh Rjadov. Forum, Moscow, Russia, 2012.

Chapters in monographs:

[1] L. Běhounek, Z. Haniková, Set theory and arithmetic in fuzzy logic. In: Petr Hájek on Mathematical Fuzzy Logic, Springer, 2014, pp..

[2] R. Bělohlávek, Formal Concept Analysis In Geology. In: Fuzzy Logic in Geology, Academic Press, USA, 2003, pp. 191-237.

[3] R. Bělohlávek, Fuzzy Galois Connections and Fuzzy Concept Lattices: From Binary Relations to Conceptual Structures. In: Discovering World With Fuzzy Logic, Springer-Verlag, Heidelberg, 2000, pp. 462-494.

[4] R. Bělohlávek, A. Dvořák, D. Jedelský, V. Novák, Object Oriented Implementation of Fuzzy Logic Systems. In: Intelligent Systems for Manufacturing. Multi-Agent Systems and Virtual Organizations, Kluwer Academic Publishers, Boston, 1998, pp. 589-594.

[5] R. Bělohlávek, T. Funioková, V. Vychodil, Galois connections with truth stressers: foundations for formal concept analysis of object-attribute data with fuzzy attributes. In: computational Intelligence, Theory and Applications, Springer, Berlin, 2005, pp. 205-219.

[6] R. Bělohlávek, I. Chajda, The intermediate property between permutability and local permutability. In: General algebra and Applications, Shaker Verlag, Aachen, 2000, pp. 19-24.

[7] R. Bělohlávek, G. Klir, R. Demicco, The role of fuzzy logic in sedimentology and stratigraphic models. In: Soft Computing and Intelligent Data Analysis in Oil Exploitation., Elsevier, USA, 2003, pp. 189-217.

[8] R. Bělohlávek, R. Tagliaferri, A. Ciaramella, A. Di Nola, Fuzzy neural networks based on fuzzy logic algebras valued relations. In: Fuzzy Partial Differential Equations and Relational Equations: Reservoir Charaterization and Modeling, Physica-Verlag, Springer, 2004, pp. 116-129.

[9] P. Drozd, M. Štěpnička, A. Dolný, P. Völkl, Fuzzy modeling – a prospective tool for conservation biology. In: Environmental changes and biological assessment III. Scripta Facultatis Rerum Naturalium Universitatis Ostraviensis Nr. 163, Ostravská univerzita v Ostravě, Ostrava, 2006, pp. 7-14.

[10] A. Dvořák, Computational Properties of Fuzzy Logic Deduction. In: Computational Intelligence. Theory and Applications. Proceedings of 5th Fuzzy Days Dortmund, Springer-Verlag, Berlin, 1997, pp. 189-196.

[11] A. Dvořák, V. Novák, Fuzzy Type Theory as a Tool for Linguistic Analysis. In: The Logica Yearbook 2006, Filosofia, Prague, 2007, pp. 51-61.

[12] A. Dvořák, V. Novák, On the Extraction of Linguistic Knowledge in Databases Using Fuzzy Logic. In: Flexible Query Answering Systems. Recent Advances, Physica-Verlag, Heidelberg, 2001, pp. 445-454.

[13] A. Dvořák, V. Novák, The Extraction of Linguistic Knowledge Using Fuzzy Logic and Generalized Quantifiers.. In: Computational Intelligent Systems for Applied Research., World Scientific, Singapore, 2002, pp. 113-120.

[14] S. Gottwald, V. Novák, I. Perfilieva, Approximating Fuzzy Control Strategies via CRI. In: Proc. of IFSA 2003, Springer-Verlag, Berlín, 2003, pp. 203-210.

[15] E.P. Klement, R. Mesiar, A. Mesiarova-Zemankova, S. Saminger, Logical connectives for granular computing. In: Handbook of Granular Computing, Wiley, Chichester, 2008, pp. 205-224.

[16] V. Novák, A Brief History of Fuzzy Logic in the Czech Republic and Significance of P. Hájek for Its Development. In: Witnessed Years, Milton Keynes, 2009, pp. 209-225.

[17] V. Novák, A Concise Glance at the History of Fuzzy Logic in Czechia. In: Logic in Central and Eastern Europe, University Press of America, Lanham, 2013, pp. 526-542.

[18] V. Novák, Formal Fuzzy Logic and Its Use in Modeling of Vagueness and Computing with Words. In: Neural Networks and Soft Computing, Springer, Heidelberg, 2003, pp. 62-72.

[19] V. Novák, Formal Theories in Fuzzy Logic. In: Fuzzy Sets, Logics, and Reasoning about Knowledge, Kluwer, Dordrecht, 1999, pp. 213-235.

[20] V. Novák, From Classical to Fuzzy Type Theory. In: The Life and Work of Leon Henkin, Birkhauser, Basel, 2014, pp. 225-248.

[21] V. Novák, Fuzzy Logic. In: Handbook of Defeasible Reasoning and Uncertainty Management Systems, Kluwer, Dordrecht, 1998, pp. 75-109.

[22] V. Novák, Fuzzy Logic: Applications to Natural Language. In: Encyclopedia of Artificial Intelligence, Second Edition, John Wiley & Sons, New York, 1992, pp. 515-521.

[23] V. Novák, Fuzzy logic deduction with words applied to ancient sea level estimation. In: Fuzzy logic in geology, Academic Press, Amsterdam, 2003, pp. 301-336.

[24] V. Novák, Fuzzy Sets in Natural Language Processing. In: Introduction to Fuzzy Logic Applications in Intelligent Systems, Kluwer, Dordrecht, 1991, pp. 185-200.

[25] V. Novák, How Ideas of L. A. Zadeh Gave Rise to Mathematical Fuzzy Logic. In: On Fuzziness, Springer, Berlin, 2013, pp. 479-486.

[26] V. Novák, Mathematical fuzzy logic: from vagueness to commonsense reasoning. In: Rehtorische Wissenschaft: Rede und Argumantation in Theorie und Praxis, Lit Verlag GmbH & Co. KG Wien, Wien, 2008, pp. 191-223.

[27] V. Novák, Mathematical fuzzy logic in modeling of natural language semantics. In: Fuzzy Logic — A Spectrum of Theoretical & Practical Issues, Springer, Berlin, 2007, pp. 145-182.

[28] V. Novák, Models and submodels of fuzzy theories. In: Intelligent Systems for Information Processing: From Representation to Applications, Elsevier, Amsterdam, 2003, pp. 363-373.

[29] V. Novák, On the Logical Basis of Approximate Reasoning. In: Fuzzy Approach to Reasoning and Decision-Making, Academia, Kluwer, Praha, Dordrecht, 1992, pp. 17-27.

[30] V. Novák, Towards Formalized Integrated Theory of Fuzzy Logic. In: Fuzzy Logic and Its Applications to Engineering, Information Sciences, and Intelligent Systems, Kluwer, Dordrecht, 1995, pp. 353-363.

[31] V. Novák, Weighted inference systems. In: Fuzzy Sets in Approximate Reasoning and Information Systems, Kluwer, Boston, 1999, pp. 191-241.

[32] V. Novák, J. Kovář, Linguistic IF-THEN Rules in Large Scale Application of Fuzzy Control. In: Fuzzy If-Then Rules in Computational Intelligence: Theory and Applications, Kluwer, Boston, 2000, pp. 223-241.

[33] V. Novák, I. Perfilieva, Evaluating Linguistic Expressions and Functional Fuzzy Theories in Fuzzy Logic. In: Computing with Words in Information/Intelligent Systems 1, Springer, Heidelberg, 1999, pp. 383-406.

[34] V. Novák, I. Perfilieva, Evaluating Linguistic Expressions and Functional Fuzzy Theories in Fuzzy Logic. In: Computing with Words in Information/Intelligent Systems 1, Springer-Verlag, Heidelberg, 1999, pp..

[35] V. Novák, I. Perfilieva, The principles of fuzzy logic: its mathematical and computational aspects. In: Lectures on Soft Computing, Springer, Heidelberg, 2001, pp. 189-238.

[36] V. Novák, I. Perfilieva, S. Gottwald, Fuzzy Relations Equations via Basic Predicate Fuzzy Logic. In: Computational Intelligent Systems for Applied Research, World Scientific, Singapore, 2002, pp. 113-120.

[37] V. Novák, I. Perfilieva, N.G. Jaruškina, A General Methodology for Managerial Decision Making using Intelligent Techniques. In: Recent Advances in Decision Making, Springer, Berlin, 2009, pp. 103-120.

[38] V. Novák, I. Perfiljeva, Mathematical Fuzzy Logic: A Good Theory for Practice. In: 35 Years of Fuzzy Set Theory: Celebratory Volume Dedicated to the Retirement of Etienne E. Kerre, Springer, Berlin, 2010, pp. 39-55.

[39] I. Perfilieva, Analytical Theory of Fuzzy IF-THEN Rules with Compositional Rule of Inference. In: Fuzzy Logic – a Spectrum of Theoretical&Practical Issues. Studies in Fuzziness and Soft Computing, Springer, Heidelberg, 2007, pp. 173-191.

[40] I. Perfilieva, Fuzzy Logic Normal Forms for Control Law Representation. In: Fuzzy Algorithms for Control, Kluwer, Boston, 1999, pp. 111-125.

[41] I. Perfilieva, Fuzzy numerical methods. In: Computational Intelligent Systems for Applied Research, World Scientific Publishing Co., Singapore, 2002, pp. 50-57.

[42] I. Perfilieva, Fuzzy Transform: Application to Reef Growth Problem. In: Fuzzy Logic in Geology, Academic Press, Amsterdam, 2003, pp. 275-300.

[43] I. Perfilieva, Fuzzy Transforms. In: Transactions on Rough Sets II. Fuzzy Sets and Rough Sets, Springer-Verlag, Berlin, 2005, pp. 63-81.

[44] I. Perfilieva, Fuzzy Transforms: A Challenge to Conventional Transforms. In: Advances in Images and Electron Physics, Elsevier Academic Press, Amsterdam, 2007, pp. 137-196.

[45] I. Perfilieva, Generic View On Continuous T-Norms and T-Conorms. In: Computational Intelligence, Theory and Applications, Springer, Heidelberg,, 2005, pp. 379-385.

[46] I. Perfilieva, Normal Forms for Fuzzy Relations and their Contribution to Universal Approximation. In: Intelligent Systems for Information Processing: From Representation to Applications, Elsevier, Amsterdam, 2003, pp. 381-392.

[47] I. Perfilieva, S. Lehmke, Safe Modeling of Fuzzy If–Then Rules. In: Computational Intelligence, Theory and Applications, Springer, Heidelberg,, 2005, pp. 235-240.

[48] I. Perfilieva, V. Novák, Some Consequences of Herbrand and McNaughton Theorems in Fuzzy Logic. In: Discovering World With Fuzzy Logic, Springer-Verlag, Heidelberg, 2000, pp. 271-295.

[49] I. Perfiljeva, M. Daňková, P. Hoďáková, M. Vajgl, F-Transform Based Image Fusion. In: Image Fusion, InTech, Rijeka, Croatia, 2011, pp. 3-22.

[50] I. Perfiljeva, J. Kupka, Bideterminant and Generalized Kronecker-Capelli Theorem for Fuzzy Relation Equations. In: Soft Computing: State of the Art Theory and Novel Applications, Springer-Verlag, Berlin, 2013, pp. 55-70.

[51] I. Perfiljeva, J. Kupka, Bideterminant and Generalized Kronecker-Capelli Theorem for Fuzzy Relation Equations. In: Soft Computing: State of the Art Theory and Novel Applications, Studies in Fuzziness and Soft Computing, Springer-Verlag, Berlin, 2013, pp. 55-70.

[52] J. Ramík, M. Vlach, Fuzzy linear programming and duality. In: Handbook o Computational Intelligence, Springer – Verlag, Berlin, Heidelberg, New York, 2015, pp. 143-162.

[53] J. Ramík, M. Vlach, Non-Controversial Definition of Fuzzy Sets. In: Transactions on Rough Sets II: Rough Sets and Fuzzy Sets, Springer, Berlin-Heidelberg-New York, 2004, pp. 201-207.

[54] R. Tagliaferri, A. Ciaramella, A. Di Nola, R. Bělohlávek, Fuzzy neural networks based on fuzzy logic algebras valued relations. In: Fuzzy Partial Differential Equations and Relational Equations: Reservoir Characterization and Modeling, Physica-Verlag, Springer, 2004, pp. 116-129.

[55] J. Tvrdík, L. Mišík, I. Křivý, Competing Heuristics in Evolutionary Algorithms. In: Intelligent Technologies-Theory and Applications, IOS Press, Amsterdam, The Netherlands, 2002, pp. 159-165.

[56] M.P. Wachowiak, R. Smolíková, M.G. Milanova, A.S. Elmagharby, Statistical nad Neural Approaches for Extimating Parameters of a Speckle Model Based on the Nakagami Distribution. In: Machine Learning and Data Mining in Pattern Recognition, Springer, Heidelberg, 2001, pp. 196-205.

Scientific journals:

[1] H. Agahi, R. Mesiar, Y. Ouyang, General Minkowski type inequalities for Sugeno integrals. FUZZY SET SYST 161 (2010) 708-715.

[2] H. Agahi, R. Mesiar, Y. Ouyang, New general extensions of Chebyshev type inequalities for Sugeno integrals. INT J APPROX REASON (2009) 135-140.

[3] T. Bacigál, V. Najjari, R. Mesiar, H. Bal, Additive generators of copulas. FUZZY SET SYST (2015) 42-50.

[4] V. BALÁŽ, L. Mišík, O. STRAUCH, J. Tóth, Distribution functions of ratio sequences IV. Period. Math. Hungar. 66 (2013) 1-22.

[5] B. Bede, H. Nobuhara, M. Daňková, A. Di Nola, Approximation by pseudo-linear operators. Fuzzy Sets and Systems 159 (2008) 804-820.

[6] B. Bede, H. Nobuhara, M. Daňková, A. Di Nola, Approximation by pseudo-linear operators. Fuzzy Sets and Systems 159 (2008) 804-820.

[7] L. Běhounek, A minimalistic many-valued theory of types. Journal of Logic and Computation (2014).

[8] L. Běhounek, Maxima and minima in fuzzified linear orderings. FUZZY SET SYST (2014).

[9] L. Běhounek, U. Bodenhofer, P. Cintula, S. Saminger-Platz, P. Sarkoci, Graded dominance and related graded properties of fuzzy connectives. FUZZY SET SYST (2014).

[10] L. Běhounek, M. Daňková, Relational compositions in Fuzzy Class Theory. FUZZY SET SYST 160 (2009) 1005-1036.

[11] R. Bělohlávek, A characterization of congruence classes of quasigroups. Mathematica Slovaca (2000) 377-380.

[12] R. Bělohlávek, A note on the extension principle. Journal of Mathematical Analysis and Applications (2000) 678-682.

[13] R. Bělohlávek, A remark on the ideal extension property. Acta Math. et Inf. Univ.Ostrav. (2001) 13-14.

[14] R. Bělohlávek, Backpropagation for interval patterns. Neural Network World (1997) 335-346.

[15] R. Bělohlávek, Birkhoff variety theorem and fuzzy logic. Arch. Math. Logic (2003) 781-790.

[16] R. Bělohlávek, Boolean part of BL-algebras. Acta Univ. Palacki Olomouc, Fac. re. nat., Mathematica (2003) 7-11.

[17] R. Bělohlávek, Combination of knowledge in fuzzy concept lattices. Int. Journal of Knowledge-Based Intelligent Engineering Systems (2002) 9-14.

[18] R. Bělohlávek, Concept equations. Journal of Logic and Computation (2004) 395-403.

[19] R. Bělohlávek, Concept lattices and order in fuzzy logic. Annals of Pure and Applied Logic (2004) 277-298.

[20] R. Bělohlávek, Concept lattices and order is uniquely given by its 1-cut: proof and consequences. Fuzzy Sets and Systems (2004) 447-458.

[21] R. Bělohlávek, Convex sets in algebras. Acta Univ. Palacki. Olomouc., Fac. rer. nat., Mathematica (2002) 21-33.

[22] R. Bělohlávek, Cutlike semantics for fuzzy logic and its applications. Int. J. General Systems (2003) 305-319.

[23] R. Bělohlávek, Determinism and fuzzy automata. Information Sciences (2002) 205-209.

[24] R. Bělohlávek, Feedforward networks with fuzzy signals. Soft Computing (1999) 37-43.

[25] R. Bělohlávek, Fuzzy closure operators. Journal of Mathematical Analysis and Applications (2001) 473-489.

[26] R. Bělohlávek, Fuzzy closure operators II. Soft Computing (2002) 53-64.

[27] R. Bělohlávek, Fuzzy closure operators induced by similarity. Fundamenta Informaticae (2003) 79-91.

[28] R. Bělohlávek, Fuzzy equational logic. Archive for Mathematical Logic (2002) 83-90.

[29] R. Bělohlávek, Fuzzy Galois connections. Math. Logic Quarterly (1999) 497-504.

[30] R. Bělohlávek, Fuzzy logical bidirectional associative memory. Information Sciences (2000) 91-103.

[31] R. Bělohlávek, Galois connections and concept lattices with globally-valued equalities. Multi.-Valued Logic (2001) 267-288.

[32] R. Bělohlávek, Lattices generated by binary fuzzy relations. Tatra Mount. Math. Publ. (1999) 11-19.

[33] R. Bělohlávek, Lattices of fixed points of fuzzy Galois connections. Mathematical Logic Quarterly (2001) 111-116.

[34] R. Bělohlávek, Logical precision in concept lattices. Journal of Logic and Computation (2002) 137-148.

[35] R. Bělohlávek, On the regularity of MV-algebras and Wajsberg hoops. Algebra Universalis (2000) 375-377.

[36] R. Bělohlávek, Poznámka ke knize Svět pojmů a logika (A note to the book uv{The world of concepts and logic}). The world of concepts and logic.

[37] R. Bělohlávek, Reduction and a simple proof of characterization of fuzzy concept lattices. Fundamenta Informaticae (2001) 277-285.

[38] R. Bělohlávek, Representation of concept lattices by bidirectional associative memories. Neural Computation (2000) 2279-2290.

[39] R. Bělohlávek, Similarity relations and BK-relational products. Information Sciences (2000) 287-295.

[40] R. Bělohlávek, Similarity relations in concept lattices. Journal of Logic and Computation (2000) 823-845.

[41] R. Bělohlávek, Some properties of residuated lattices. Czechoslovak Mathematical Journal (2003) 161-171.

[42] R. Bělohlávek, The block extension property. It. Journal of Pure and Applied Mathematics (2001) 147-151.

[43] R. Bělohlávek, T. Funioková, Fuzzy interior operators. Journal of General Systems (2004) 315-330.

[44] R. Bělohlávek, T. Funioková, Similarity and fuzzy tolerance spaces. Journal of Logic and Computation (2004) 827-855.

[45] R. Bělohlávek, T. Funioková, Similarity and fuzzy tolerance spaces. Journal of Logic and Computation (2006) 827-855.

[46] R. Bělohlávek, I. Chajda, A polynomial characterization of congruence classes. Algebra Universalis (1997) 235-242.

[47] R. Bělohlávek, I. Chajda, Congruence classes in regular varieties. Acta Math. Univ. Comen. (1999) 71-75.

[48] R. Bělohlávek, I. Chajda, Congruence Properties in Single Algebras. Discuss. Math. (1997) 67-78.

[49] R. Bělohlávek, I. Chajda, Relative deductive systems and congruence classes. Multiple-Valued Logic (2000) 259-266.

[50] R. Bělohlávek, I. Chajda, The block extension property. Journal of Pure and Applied Mathematics (2001) 147-151.

[51] R. Bělohlávek, G. Klir, I.H.W. Lewis, E. Way, On the capability of fuzzy set theory to represent concepts. Journal of General Systems (2002) 569-585.

[52] R. Bělohlávek, V. Novák, Learning rule base in linguistic expert systems. Soft Computing (2002) 79-88.

[53] R. Bělohlávek, V. Sklenář, J. Zacpal, Formal concept analysis with hierarchically ordered attributes. Journal of General Systems (2004) 283-294.

[54] J. Boroński, On the number of orbits of the homeomorphism group of solenoidal spaces. TOPOL APPL (2015) 98-106.

[55] J. Boroński, P. Oprocha, ON ENTROPY OF GRAPH MAPS THAT GIVE HEREDITARILY INDECOMPOSABLE INVERSE LIMITS. Proceedings of the Japan Academy, Series A (submitted) (2014).

[56] J. Boroński, P. Oprocha, On indecomposability in chaotic attractors. Proceedings of the American Mathematical Society (2014).

[57] J. Boroński, P. Oprocha, ROTATIONAL CHAOS AND STRANGE ATTRACTORS ON THE 2-TORUS. MATH Z (2015) 689-702.

[58] J. Boroński, F. Sturm, Finite-sheeted covering spaces and a Near Local Homeomorphism Property for pseudosolenoids. TOPOL APPL 161 (2013) 235-242.

[59] A. Bronevich, R. Mesiar, Invariant continuous aggregation functions. INT J GEN SYST 2 (2010) 177-188.

[60] J. Bukor, L. Mišík, J. Tóth, On mappings preserving measurability. INFORM SCIENCES 235 (2013) 323-328.

[61] M. Burda, P. Rusnok, M. Štěpnička, Mining Linguistic Associations for Emergent Flood Prediction Adjustment. Advances in Fuzzy Systems 2013 (2013) 1-10.

[62] H. Bustince, B. De Baets, J. Fernandez, R. Mesiar, J. Montero, A generalization of the migrativity property of aggregation functions. INFORM SCIENCES 191 (2012) 76-85.

[63] H. Bustince, J. Fernandez, A. Kolesárová, R. Mesiar, Directional monotonicity of fusion functions. (2014).

[64] H. Bustince, J. Fernandez, J. Sanz, M. Baczynski, R. Mesiar, Construction of strong equality index from implication operators. FUZZY SET SYST 211 (2013) 15-33.

[65] H. Bustince, A. Jurio, A. Pradera, R. Mesiar, G. Beliakov, Generalization of the weighted voting method using penalty functions constructed via faithful restricted dissimilarity functions. EUR J OPER RES 225 (2013) 472-478.

[66] H. Bustince, N.M. Madrid, M. Ojeda-Aciego, The notion of weak-contradiction: definition and measures. IEEE Transaction Fuzzy Systems (2014) 1-13.

[67] A. Cena, M. Gagolewski, R. Mesiar, Problems and challenges of information resourcesproducers? clustering. J INFORMETR 9 (2015) 273-284.

[68] P. Cintula, E.P. Klement, R. Mesiar, M. Navara, Fuzzy logics with an additional involutive negation. FUZZY SET SYST (2010) 390-411.

[69] P. Cintula, E.P. Klement, R. Mesiar, M. Navara, Residuated logics based on strict triangular norms with an involutive negation. Math. Logic Quarterly 6 (2006) 269-282.

[70] M. Daňková, Approximation of extensional fuzzy relations over a residuated lattice. FUZZY SET SYST 161 (2010) 1973-1991.

[71] M. Daňková, Extensionality and Continuity of Fuzzy Relations. Journal of electrical engineering 12 (2000) 33-35.

[72] M. Daňková, Generalized extensionality of fuzzy relations. FUZZY SET SYST 148 (2004) 291-304.

[73] M. Daňková, Normal forms for fuzzy logic functions. Journal of electrical engineering 12 (2003) 80-84.

[74] M. Daňková, On approximate reasoning with graded rules. FUZZY SET SYST 158 (2007) 652-673.

[75] M. Daňková, On approximate reasoning with graded rules. FUZZY SET SYST 158 (2007) 652-673.

[76] M. Daňková, Representation of Logic Formulas by Normal Forms. KYBERNETIKA 38 (2002) 717-728.

[77] M. Daňková, A. Dvořák, Characterization and approximate representation of extensional fuzzy relations. Journal of Electrical Engineering 12 (2004) 51-55.

[78] M. Daňková, I. Perfilieva, Logical Approximation II. SOFT COMPUT 7 (2003) 228-233.

[79] M. Daňková, M. Štěpnička, Fuzzy Transform as an Additive Normal Form. FUZZY SET SYST 157 (2006) 1024-1035.

[80] M. Daňková, R. Valášek, Full Fuzzy Transform and the Problem of Image Fusion. Journal of electrical engineering 12 (2006) 82-84.

[81] B. De Baets, H. De Meyer, R. Mesiar, Binary survival aggregation functions. FUZZY SET SYST (2012) 83-102.

[82] B. De Baets, H. De Meyer, R. Mesiar, Lipschitz continuity of copulas wrt Lp-norms. NONLINEAR ANAL-THEOR 72 (2010) 3722-3731.

[83] B. De Baets, H. Demeyer, R. Mesiar, Asymmetric semilinear copulas. Kybernetika 43 (2007) 221-233.

[84] B. De Baets, H. Demeyer, R. Mesiar, Asymmetric semilinear copulas. Kybernetika 43 (2007) 221-233.

[85] B. Debaets, H. Demeyer, J. Kalicka, R. Mesiar, Flipping and cyclic shifting of binary aggregation functions. Fuzzy Sets and Systems (2009) 752-765.

[86] B. DeBaets, H. DeMeyer, J. Kalicka, R. Mesiar, On the relationship between modular functions and copulas. FUZZY SET SYST (2014).

[87] F. Di Martino, V. Loia, I. Perfilieva, S. Sessa, An image coding/decoding method based on direct and inverse fuzzy transforms. International Journal of Appr. reasoning 48 (2008) 110-131.

[88] F. Di Martino, V. Loia, I. Perfilieva, S. Sessa, An image coding/decoding method based on direct and inverse fuzzy transforms. International Journal of Appr. reasoning 48 (2008) 110-131.

[89] A. Di Nola, A. Lettieri, V. Novák, I. Perfilieva, Algebraic Analysis of Fuzzy Systems. Fuzzy Sets and Systems 158 (2007) 1-22.

[90] A. Di Nola, A. Lettieri, V. Novák, I. Perfilieva, Algebraic Analysis of Fuzzy Systems. Fuzzy Sets and Systems 158 (2007) 1-22.

[91] F. Durante, E.P. Klement, R. Mesiar, C. Sempi, Conjunctors and their residual implicators: characterizations and construction methods. Mediterranian Journal of Mathematics 4 (2007) 343-356.

[92] F. Durante, E.P. Klement, R. Mesiar, C. Sempi, Conjunctors and their residual implicators: characterizations and construction methods. Mediterranian Journal of Mathematics 4 (2007) 343-356.

[93] F. Durante, R. Mesiar, P.L. Papini, The lattice-theoretic structure of the sets of triangular norms and semi-copulas. NONLINEAR ANAL-THEOR 69 (2008) 46-52.

[94] F. Durante, R. Mesiar, P.L. Papini, The lattice-theoretic structure of the sets of triangular norms and semi-copulas. NONLINEAR ANAL-THEOR 69 (2008) 46-52.

[95] A. Dvořák, On Linguistic Approximation in the Frame of Fuzzy Logic Deduction. Soft Computing 3 (1999) 111-116.

[96] A. Dvořák, On Preselection of Rules in Fuzzy Logic Deduction. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 8 (2000) 563-572.

[97] A. Dvořák, H. Habiballa, V. Novák, V. Pavliska, The concept of LFLC 2000 – its specificity, realization and power of applications. COMPUT IND 51 (2003) 269-280.

[98] A. Dvořák, M. Holčapek, Fuzzy measures and integrals defined on algebras of fuzzy subsets over complete residuated lattices. INFORM SCIENCES 185 (2012) 205-229.

[99] A. Dvořák, M. Holčapek, L-fuzzy Quantifiers of Type <1> Determined by Fuzzy Measures. FUZZY SET SYST 160 (2009) 3425-3452.

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[462] J. Žáček, F. Huňka, Reusable object-oriented model. e-Informatica Software Engineering Journal 7 (2013) 35-44.

[463] A. Žák, M. Burda, M. Vecka, M. Zeman, E. Tvrznická, B. Staňková, Fatty Acid Composition Indicates the Two Types of Metabolic Syndrome Independently on Clinical and Laboratory Parameters. Physiological Research 63 (2014) 375-385.

Conference proceedings:

[1] R. Bělohlávek, Algorithms for fuzzy concept lattices. In: Proc. Fourth Int. Conf. on Recent Advances in Soft Computing, Nottingham, United Kingdom, 2002, pp. 67-68.

[2] R. Bělohlávek, Cutlike semantics for fuzzy logic. In: Proc. Fourth Ing. Cong. on Recent Advances in Soft Computing, Nottingham, United Kingdom, 2002, pp. 135-136.

[3] R. Bělohlávek, Fuzzy closure operators induced by similarity. In: Heidelberg, 2003, pp. 71-78.

[4] R. Bělohlávek, Koncepruální svazy a formální konceptuální analýza. In: 2004, pp. 66-84.

[5] R. Bělohlávek, Lattice type fuzzy order and clocure operators in fuzzy ordered sets. In: Proc. Joint 9th IFSA World Congress and 20th NAFIPS International Conference, Vancouver, Canada, 2001, pp. 2281-2286.

[6] R. Bělohlávek, Logical precision in conceptual structures. In: Genova, Italy, 1999, pp. 619-623.

[7] R. Bělohlávek, Model theory for fuzzy logic in the foundations of soft computing. In: Proc. IEEE Systems, Man and Cybernetics 2000 Conference, Nashville, Tennessee, USA, 2000, pp. 3635-3640.

[8] R. Bělohlávek, Multilayer neural networks with fuzzy signals – adaptation and some remarks. In: Proc. VIIth IFSA World Congress Prague, Praha, 1977, pp. 537-542.

[9] R. Bělohlávek, V. Novák, Learning Linguistic Context for Linguistic Oriented Fuzzy Control. In: Proc. Int. Conference FUZZ-IEEE’97, Barcelona, 1997, pp. 1167-1168.

[10] R. Bělohlávek, V. Sklenář, J. Zacpal, Concept lattices constrained by attribute dependencies. In: Proc. DATESO 2004, CEUR Workshop Proceedings, 2004, pp. 63-73.

[11] R. Bělohlávek, V. Sklenář, J. Zacpal, Expressive capability of AD-formulas in constraning concept lattices. In: 2004, pp. 201-210.

[12] R. Bělohlávek, V. Snášel, Podobnost a její modelování. In: 2004, pp. 309-316.

[13] R. Bělohlávek, V. Vychodil, Algebras with fuzzy equalities. In: Istanbul, Turkey, 2003, pp. 1-4.

[14] P. Berruet, T. Coudert, E. Kindler, Component-Based Simulation – a View From Transitic System Models. In: Proc. ASIS’04 – Advanced Simulation of Systems, Ostrava, 2004, pp. 259-264.

[15] P. Berruet, T. Coudert, E. Kindler, Conveyors with rollers as anticipatory systems: Their simulation models. In: Proc. CASYS 2003 / Sixth International Conference, Melville, USA, 2004, pp. 582-592.

[16] P. Berruet, T. Coudert, E. Kindler, Vers une simulation reflective en ingenerie des systemes transitiques. In: Proc. MOSIM’04 – 5me Conference francophone de Mode;lisation et Simulation, Nantes, 2004, pp. 149-156.

[17] J. Blažek, H. Habiballa, V. Pavliska, Vybrané heuristiky pro globální optimalizaci a jejich implementace v MATLABu. In: Proc. Technical Computing Prague 2005, Praha, 2005, pp. 19-19.

[18] U. Bodenhofer, M. Daňková, M. Štěpnička, V. Novák, A Plea for the Usefulness of the Deductive Interpretation of Fuzzy Rules in Engineering Applications. In: Proc. FUZZ-IEEE, London, 2007, pp. 1572-1577.

[19] M. Burda, M. Štěpnička, L. Štěpničková, Fuzzy Rule-Based Ensemble for Time Series Prediction: Progresses with Associations Mining. In: Proc. Soft Methods in Probability and Statistics, Heidelberg, 2015, pp. 261-271.

[20] H. Bustince, J. Fernandez, D. Paternain, M. Baczynski, G. Beliakov, R. Mesiar, J.A. Sanz, Construction of strong equality index from implication operators. In: Proc. FLINS2012, New Jersey, 2012, pp. 769-774.

[21] H. Bustince, J. Fernandez, D. Paternain, M. Baczynski, G. Beliakov, R. Mesiar, J.A. Sanz, Construction of strong equality index from implication operators. In: Proc. FLINS2012, New Jersey, 2012, pp. 769-774.

[22] P. Cintula, E.P. Klement, R. Mesiar, M. Navara, Varieties of algebras based on strict t-norms and involutive negations. In: Proc. 8th FSTA, Liptovsky Mikulas, 2006, pp. 8-9.

[23] M. Daňková, Extensionality and Continuity. In: Proc. EUSFLAT 2003, Zittau, 2003, pp. 624-629.

[24] M. Daňková, Extensionality as a basis for fuzzy approximation. In: Proc. 8th International Conference on Fuzzy Set Theory an Applications FSTA’06, Liptovský Mikuláš, Slovensko, 2006, pp. 34-34.

[25] M. Daňková, Fuzzy Functions and Their Representations in Fuzzy Class Theory. In: Proc. NCMPL 2011, Prague, 2011, pp. 52-57.

[26] M. Daňková, Generalized Implicative Model of a Fuzzy Rule Base and its Properties. In: Proc. Cognitive 2011, 2011, pp. 116-121.

[27] M. Daňková, Generalized Implicative Model of a Fuzzy Rule Base and its Properties. In: Proc. Cognitive 2011, 2011, pp. 116-121.

[28] M. Daňková, Graded fuzzy rules. In: Proc. IFSA 2007, Heidelberg, 2007, pp. 481-490.

[29] M. Daňková, Graded fuzzy rules for functional dependencies: Normal form based formalization. In: Proc. IFSA 2011, Surabaya, 2011, pp. 2121-2126.

[30] M. Daňková, Graded fuzzy rules for functional dependencies: Normal form based formalization. In: Proc. IFSA 2011, Surabaya, 2011, pp. 2121-2126.

[31] M. Daňková, Integral based aggregation operators in the theory of fuzzy approximation. In: Hagenberg, 2006, pp. 23-31.

[32] M. Daňková, Normal forms based fuzzy systems. In: Proc. Joint EUSFLAT – LFA 2005, Barcelona, 2005, pp. 633-638.

[33] M. Daňková, REPRESENTATION THEOREM FOR FUZZY FUNCTIONS — Graded form. In: Proc. INTERNATIONAL CONFERENCE ON FUZZY COMPUTATION 2010, Portugal, 2010, pp. 56-64.

[34] M. Daňková, B. Bede, Aggregation Operators Based Fuzzy Approximations. In: Proc. INES2006, Londýn, 2006, pp. 154-159.

[35] M. Daňková, B. Bede, Aggregation Operators Based Fuzzy Approximations. In: Proc. INES2006, Londýn, 2006, pp. 154-159.

[36] M. Daňková, L. Běhounek, Automated proofs for composition-based fuzzy relational notions. In: Proc. Logic of Soft Computing 5 & 5th workshop of the ERCIM working group of Soft Computing, Malaga, 2006, pp. 96-102.

[37] M. Daňková, L. Běhounek, Relation Compositions in Fuzzy Class Theory. In: Proc. 8th International Conference on Fuzzy Set Theory an Applications FSTA’06, Liptovský Mikuláš, Slovensko, 2006, pp. 23-23.

[38] M. Daňková, I. Štajner-Papuga, B. Bede, Pseudo-Fourier transform. In: Proc. SISY, Subotica, 2006, pp. 145-153.

[39] M. Daňková, I. Štajner-Papuga, D. Hliněná, Pseudo Riemann-Stielties integral based Fourier transform. In: Proc. APLIMAT 2007, Bratislava, 2007, pp. 373-381.

[40] M. Daňková, M. Štěpnička, Approximation properties of inverse fuzzy transforms over a residuated lattice. In: Proc. IFSA/EUSFLAT’09, Lisabon, 2009, pp. 693-696.

[41] M. Daňková, M. Štěpnička, Genetic algorithms in fuzzy approximation. In: Proc. Joint EUSFLAT – LFA 2005, Barcelona, 2005, pp. 651-656.

[42] M. Daňková, M. Štěpnička, B. De Baets, Grades of monotonicity of fuzzy relations and their application to fuzzy rule bases. In: Proc. IEEE Symposium on Foundations of Computational Intelligence, Paris, 2011, pp. 37-44.

[43] M. Daňková, M. Štěpnička, B. De Baets, Grades of monotonicity of fuzzy relations and their application to fuzzy rule bases. In: Proc. IEEE Symposium on Foundations of Computational Intelligence, Paris, 2011, pp. 37-44.

[44] M. Daňková, M. Štěpnička, B. De Baets, Monotonicity of fuzzy rule bases: On differences between graded and non-graded approaches. In: Proc. EUSFLAT 2011, 2011, pp. 487-492.

[45] M. Daňková, R. Valášek, Image fusion using fuzzy transform. In: Hagenberg/Linz, 2006, pp. 49-53.

[46] F. Durante, E.P. Klement, R. Mesiar, C. Sempi, Conjunctors and their residual implicators. In: Proc. Fuzzy Sets, Probability, and Statistics – Gaps and Bridges, Linz, Rakousko, 2007, pp. 46-50.

[47] A. Dvořák, On Linguistic Approximation in the Frame of LFLC. In: Proc. IFSA 97, Prague, 1997, pp. 412-417.

[48] A. Dvořák, Properties of the Generalized Fuzzy Logic Inference. In: Proc. SIC’96 Budapest, Budapest, 1996, pp. 75-80.

[49] A. Dvořák, H. Habiballa, V. Pavliska, V. Novák, LFLC 2000 + MATLAB/SIMULINK – SYSTÉM PRO UNIVERSÁLNÍ APLIKACE FUZZY LOGIKY. In: Proc. Inteligentní systémy v praxi, Ostrava, 2003, pp. 47-48.

[50] A. Dvořák, M. Holčapek, A Characterization of Fuzzy Integrals Invariant with Respect to Permutation Groups. In: Proc. 14th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, Heidelberg, 2012, pp. 208-217.

[51] A. Dvořák, M. Holčapek, A Characterization of Fuzzy Integrals Invariant with Respect to Permutation Groups. In: Proc. 14th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, Heidelberg, 2012, pp. 208-217.

[52] A. Dvořák, M. Holčapek, Fuzzy integrals over complete residuated lattices. In: Proc. IFSA 2009 World Congress EUSFLAT 2009 World Conference, Lisabon, 2009, pp. 357-362.

[53] A. Dvořák, M. Holčapek, Fuzzy Measure Spaces Generated by Fuzzy Sets. In: Proc. 13th International Conference on Information Processing and Management of Uncertainty, Heidelberg, 2010, pp. 490-499.

[54] A. Dvořák, M. Holčapek, On Convergence of Fuzzy Integrals over Complete Residuated Lattices. In: Proc. EUSFLAT 2011, 2011, pp. 98-105.

[55] A. Dvořák, M. Holčapek, On Convergence of Fuzzy Integrals over Complete Residuated Lattices. In: Proc. EUSFLAT 2011, 2011, pp. 98-105.

[56] A. Dvořák, D. Jedelský, Defuzzification and Chaining of Rules in Hierarchical Fuzzy Systems. In: Proc. 1999 Eusflat-Estylf Joint Conference, Palma de Mallorca, 1999, pp. 199-202.

[57] A. Dvořák, V. Novák, A Fuzzy Logic Model of Detective Reasoning. In: Proc. IMPU’06, Paris, 2006, pp. 1572-1579.

[58] A. Dvořák, V. Novák, Automation of Human Reasoning in Economical Analysis. In: Proc. EUSFLAT 2007, Ostrava, 2007, pp. 103-109.

[59] A. Dvořák, V. Novák, Fuzzy Logic as a Methodology for the Treatment of Vagueness. In: Proc. logica 2004, Praha, 2005, pp. 141-152.

[60] A. Dvořák, V. Novák, Inconsistencies in Linguistic Descriptions from the Point of View of Fuzzy Logic. In: Proc. Third Conf. EUSFLAT 2003, Zittau/Goerlitz, 2003, pp. 523-528.

[61] A. Dvořák, V. Novák, V. Pavliska, H. Habiballa, LFLC 2000 + MATLAB/SIMULINK – SYSTÉM PRO UNIVERSÁLNÍ APLIKACE FUZZY LOGIKY. In: Proc. Matlab, Praha, 2002, pp. 80-85.

[62] A. Dvořák, M. Štěpnička, L. Vavříčková, Redundancies in systems of fuzzy/linguistic IF-THEN rules. In: Proc. EUSFLAT 2011, 2011, pp. 1022-1029.

[63] M. Dyba, V. Novák, On EQ-fuzzy logics with delta connective. In: Proc. EUSFLAT 2011, Amsterdam, 2011, pp. 156-162.

[64] R. Farana, B. Walek, M. Janošek, J. Žáček, Fuzzy-Logic Control in Fast Technological Processes. In: Proc. 15th International Carpathian Control Conference, ICCC 2014, Velké Karlovice, 2014, pp. 105-108.

[65] R. Farana, B. Walek, M. Janošek, J. Žáček, Fuzzy-Logic Control in Fast Technological Processes. In: Proc. 15th International Carpathian Control Conference, ICCC 2014, Velké Karlovice, 2014, pp. 105-108.

[66] R. Ghiselli-Ricci, R. Mesiar, k-Lipschitz strict triangular norms. In: Proc. EUSFLAT-LFA 2005, Barcelona, 2005, pp. 1307-1312.

[67] R. Ghiselli-Ricci, R. Mesiar, A. Mesiarová, Lipschitzianity of triangular subnorms. In: Proc. IPMU’2006, Paris, 2006, pp. 671-677.

[68] S. Gottwald, V. Novák, On the Consistency of Fuzzy Theories. In: Proc. VIIth IFSA World Congress, Praha, 1997, pp. 168-171.

[69] S. Gottwald, V. Novák, I. Perfilieva, Fuzzy control and pseudo-solutions of fuzzy relation equations. In: Zittau, Germany, 2002, pp. 12-18.

[70] S. Gottwald, V. Novák, I. Perfilieva, Fuzzy Control and t-norm-Based Fuzzy Logic. Some Recent Results. In: Proc. IPMU 2002, Annecy, 2002, pp. 1087-1094.

[71] T. Grbic, M. Daňková, I. Štajner-Papuga, Properties of the pseudo Riemann-Stiltjes integral. In: Proc. International Conference on Fuzzy Set Theory and Its Applications, Liptovský Ján, 2008, pp. 47-47.

[72] H. Habiballa, FUZZY PREDICATE LOGIC AND RESOLUTION THEOREM PROVING. In: Proc. 4 th Mathematical Conference, Nitra, 2006, pp. 79-85.

[73] H. Habiballa, INFERENCE METHODS FOR FUZZY PREDICATE LOGIC BASED ON RESOLUTION PRINCIPLE. In: Proc. Aplimat 2007, Bratislava, 2007, pp. 525-534.

[74] H. Habiballa, Non-clausal Resolution in Fuzzy Predicate Logic with Evaluated Syntax (background and implementation). In: Proc. The Logic of Soft Computing IV, Ostrava, 2005, pp. 51-54.

[75] H. Habiballa, Resolution Principle in Fuzzy Predicate Logic. In: Trnava, 2005, pp. 3-12.

[76] H. Habiballa, Resolution Principle in Fuzzy Predicate Logic. In: Proc. Aplimat 2006, Bratislava, 2006, pp. 525-534.

[77] H. Habiballa, Resolution Strategies for Fuzzy Description Logic. In: Proc. EUSFLAT, Ostrava, 2007, pp. 27-36.

[78] H. Habiballa, Resolution strategies for fuzzy predicate logic with evaluated syntax. In: Proc. ZNALOSTI 2007, Ostrava, 2007, pp. 201-212.

[79] H. Habiballa, Resolution strategies in fuzzy description logic. In: Proc. APLIMAT, Bratislava, 2008, pp. 523-532.

[80] H. Habiballa, V. Novák, Fuzzy General Resolution. In: Proc. Aplimat 2002, Bratislava, 2002, pp. 199-206.

[81] H. Habiballa, V. Novák, Character recognition through fuzzy logic analysis – Algorithms and Implementation. In: Proc. APLIMAT, Bratislava, 2013, pp. 541-550.

[82] H. Habiballa, V. Novák, A. Dvořák, V. Pavliska, Využití softwarového balíku LFLC 2000. In: Proc. 2nd International Conference Aplimat 2003, Bratislava, 2003, pp. 355-358.

[83] H. Habiballa, V. Novák, M. Dyba, J. SCHENK, EQ-ALGEBRAS AUTOMATED GENERATION BASED ON GENETIC ALGORITHMS. In: Proc. MENDEL, Brno, 2014, pp. 341-346.

[84] H. Habiballa, V. Novák, M. Dyba, J. SCHENK, EQ-ALGEBRAS AUTOMATED GENERATION BASED ON GENETIC ALGORITHMS. In: Proc. MENDEL, Brno, 2014, pp. 341-346.

[85] H. Habiballa, V. Pavliska, D. Bražina, Objektová knihovna evolučních algoritmů. In: Proc. Tvorba softwaru, Ostrava, 2005, pp. 18-24.

[86] H. Habiballa, V. Pavliska, A. Dvořák, Software system for time series prediction based on F-transform and linguistic rules. In: Proc. 8th International Conference on Applied Mathematics APLIMAT 2009, Bratislava, 2009, pp. 381-386.

[87] J. Hančl, L. Mišík, J. Tóth, Fuzzy rational numbers and approximation of irrationals. In: Proc. Workshop of the ERCIM working group on Soft Computing, Malaga, 2006, pp. 5-8.

[88] J. Hančl, L. Mišík, J. Tóth, Fuzzy rational numbers and approximation of irrationals. In: Proc. Eight International Conference on Fuzzy Set Theory and Applications FSTA 2006, Liptovský Ján, 2006, pp. 51-51.

[89] J. Hančl, L. Mišík, J. Tóth, Fuzzy rational numbers and approximation of irrationals. In: Proc. Eight International Conference on Fuzzy Set Theory and Applications FSTA 2006, Liptovský Ján, 2006, pp. 51-51.

[90] J. Hančl, L. Mišík, J. Tóth, Limit points of sequences of fuzzy real numbers. In: Proc. 28th Linz Seminar on Fuzzy Set Theory, Linz, 2007, pp. 66-69.

[91] P. Hoďáková, I. Perfiljeva, Fverb_^_1-transform of Functions of Two Variables. In: Proc. 8th Conference of the European Society for Fuzzy Logic and Technology, EUSFLAT 2013, Paris, France, 2013, pp. 547-553.

[92] P. Hoďáková, I. Perfiljeva, P. Hurtík, F-transform and Its Extension as Tool for Big Data Processing. In: Proc. 15th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems (IPMU 2014), 2014, pp. 374-383.

[93] P. Hoďáková, I. Perfiljeva, P. Hurtík, F-transform and Its Extension as Tool for Big Data Processing. In: Proc. 15th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems (IPMU 2014), 2014, pp. 374-383.

[94] P. Hoďáková, M. Vajgl, I. Perfiljeva, M. Daňková, Classification of Damages on Jewelry Stones: Preprocessing. In: Proc. 9th Joint World Congress on Fuzzy Systems and NAFIPS Annual Meeting, IFSA/NAFIPS 2013, Edmonton, Canada, 2013, pp. 783-788.

[95] P. Hoďáková, M. Vajgl, I. Perfiljeva, M. Daňková, Classification of Damages on Jewelry Stones: Preprocessing. In: Proc. 9th Joint World Congress on Fuzzy Systems and NAFIPS Annual Meeting, IFSA/NAFIPS 2013, Edmonton, Canada, 2013, pp. 783-788.

[96] P. Hoďáková, M. WRUBLOVÁ, I. Perfiljeva, Fuzzy Rule Base Interpolation and its Graphical Representation. In: Proc. 17th Zittau East-West Fuzzy Colloquium, Zittau/Görlitz, 2010, pp. 132-137.

[97] M. Holčapek, An Axiomatic Approach to Fuzzy Measures Like Set Cardinality for Finite Fuzzy Sets. In: Proc. 13th International Conference on Information Processing and Management of Uncertainty, Heidelberg, 2010, pp. 505-514.

[98] M. Holčapek, Fuzzy logic with fuzzy quantifiers. In: Proc. IPMU 2006 (IInformation Processing and Management of Uncertainty in Knowledge-based Systems), Paris, 2006, pp. 1882-1889.

[99] M. Holčapek, Fuzzy quantifiers. In: Proc. 8th International Conference on Fuzzy Set Theory an Applications FSTA’06, Liptovský Mikuláš, Slovensko, 2006, pp. 55-56.

[100] M. Holčapek, Fuzzy quantifiers. In: Proc. 8th International Conference on Fuzzy Set Theory an Applications FSTA’06, Liptovský Mikuláš, Slovensko, 2006, pp. 55-56.

[101] M. Holčapek, Graded Equipollence And Fuzzy C-measures Of Finite Fuzzy Sets. In: Proc. 2011 IEEE International Conference on Fuzzy Systems, Taiwan, 2011, pp. 2375-2382.

[102] M. Holčapek, Graded Equipollence of L-fuzzy sets. In: Proc. International Conference on Fuzzy Set Theory and Applications – FSTA, Liptovský Ján, 2008, pp. 53-54.

[103] M. Holčapek, Monadic L-fuzzy quantifiers of the type <1verb_^_n,1>. In: Proc. 5th EUSFLAT, Ostrava, 2007, pp. 409-415.

[104] M. Holčapek, A. Dvořák, On Monotonicity Of Type <1, 1> Fuzzy Quantifiers Determined By Fuzzy Measures. In: Proc. 2011 IEEE International Conference on Fuzzy Systems, Taiwan, 2011, pp. 2383-2390.

[105] M. Holčapek, A. Dvořák, Type <1, 1> Fuzzy Quantifiers Determined by Fuzzy Measures. In: Proc. IEEE World Congress on Computational Intelligence, Barcelona, 2010, pp. 3168-3175.

[106] M. Holčapek, A. Dvořák, Type <1,1> Fuzzy Quantifiers Determined by Fuzzy Measures. In: Proc. 13th Czech-Japan seminar on data analysis and decision making in service sciences, Otaru, Japan, 2010, pp. 1-6.

[107] M. Holčapek, V. Kreinovich, Processing Quantities with Heavy-Tailed Distribution of Measurement Uncertainty: How to Estimate the Tails of the Results of Data Processing. In: Proc. WSCS 2013, New York, 2014, pp. 25-32.

[108] M. Holčapek, I. Perfiljeva, V. Novák, Discrete Representation of Stationary Random Processes Using Fuzzy Transform. In: Proc. 16th Czech-Japan Seminar on Data Analysis and Decision Making under Uncertainty, Plzeň, 2013, pp. 215-222.

[109] M. Holčapek, I. Perfiljeva, V. Novák, Discrete Representation of Stationary Random Processes Using Fuzzy Transform. In: Proc. 16th Czech-Japan Seminar on Data Analysis and Decision Making under Uncertainty, Plzeň, 2013, pp. 215-222.

[110] M. Holčapek, M. Štěpnička, Arithmetics of Extensional Fuzzy Numbers — Part II: Algebraic framework. In: Proc. FUZZ-IEEE, 2012, pp. 1525-1532.

[111] M. Holčapek, M. Štěpnička, Arithmetics of Extensional Fuzzy Numbers — Part II: Algebraic framework. In: Proc. FUZZ-IEEE, 2012, pp. 1525-1532.

[112] M. Holčapek, T. Tichý, A comparison of smoothing filter based on fuzzy transform and Nadaraya-Watson estimators. In: Proc. Mathematical Methods in Economics, Praha: VŠE Praha, 2011, pp. 260-265.

[113] M. Holčapek, T. Tichý, Simulation methodology for financial assets with imprecise data. In: Proc. Mathematical Methods in Economics, Praha: VŠE Praha, 2011, pp. 709-714.

[114] M. Holčapek, T. Tichý, Statistical analysis of a smoothing filter based on fuzzy transform. In: Proc. EUSFLAT 2011, 2011, pp. 472-479.

[115] M. Holčapek, M. Turčan, Graded Equipollence of Fuzzy Sets. In: Proc. IFSA 2009 World Congress EUSFLAT 2009 World Conference, Lisabon, 2009, pp. 1565-1570.

[116] M. Holčapek, M. Turčan, Operations with General Fuzzy Decision Systems. In: Proc. 8th International Conference on Fuzzy Set Theory an Applications FSTA’06, Liptovský Mikuláš, Slovensko, 2006, pp. 106-107.

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[118] F. Huňka, Anticipation models in Beta. In: Proc. CASYS ’05, Liege, Belgie, 2005, pp. 14-14.

[119] F. Huňka, Anticipation Models in BETA. In: Proc. CASYS ‘ 05 Computing Anticipatory Systems, Liege, 2005, pp. 14-14.

[120] F. Huňka, Anticipation Models in BETA. In: Proc. 7th International Conference on Computing Anticipatory Systems (CASYS 05), Melville, New York, USA, 2006, pp. 354-360.

[121] F. Huňka, Anticipation Models in BETA. In: Proc. 7th International Conference on Computing Anticipatory Systems (CASYS 05), Melville, New York, USA, 2006, pp. 354-360.

[122] F. Huňka, BETA as Agent Based Simulation Language. In: Proc. 20th European Conference on Modelling and Simulation, Bonn Německo, 2006, pp. 521-525.

[123] F. Huňka, BetaSIM Extended Simulation Framework for General Discrete Event Simulation. In: Proc. Industrial Simulation Conference 2005, Berlin, 2005, pp. 159-162.

[124] F. Huňka, Making BETA to System Simulation. In: Proc. 21 st European Conference on Operational Research, Reykjavik, 2006, pp. 98-98.

[125] F. Huňka, Making BETA to System Simulation. In: Proc. 21 st European Conference on Operational Research, Reykjavik, 2006, pp. 98-98.

[126] F. Huňka, Object Oriented Approach in Fuzzy Arithmetic Using Parametric Representation of Fuzzy Numbers. In: Proc. New Dimensions in Fuzzy Logic and Related Technologies, Ostrava, 2007, pp. 273-278.

[127] F. Huňka, Object Oriented Software for Fuzzy Arithmetic. In: Proc. CASYS 07, Liege, 2007, pp. 31-32.

[128] F. Huňka, V. Pavliska, Object Oriented Approach in Optimization of Fuzzy Transform. In: Proc. WSEAS International Conference on Computers, Heraklion, 2008, pp. 1066-1071.

[129] F. Huňka, J. Ráček, Object Oriented Model for Cluster Analysis in Environmental Risk Management. In: Proc. EnviroInfo, Brno, 2005, pp. 446-452.

[130] P. Hurtík, Algoritmy pro detekci rohů a měření podobnosti aplikované na problematiku superresolution. In: Proc. Studentská vědecká konference, 2013, pp..

[131] P. Hurtík, Algoritmy pro detekci rohů a měření podobnosti aplikované na problematiku superresolution. In: Proc. Studentská vědecká konference, 2013, pp..

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[133] P. Hurtík, I. Perfiljeva, Image compression methodology based on fuzzy transform. In: Proc. SOCO 2012, Berlin, 2013, pp. 525-532.

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[135] P. Hurtík, I. Perfiljeva, Image compression methodology based on fuzzy transform using block similarity. In: Proc. EUSFLAT 2013, 2013, pp. 521-526.

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