Institute of Information Engineering, Automation, and Mathematics

doc. RNDr. Zdenko Takáč, PhD.

Position:
Lecturer
Department:
Department of Mathematics (DM)
Room:
NB 615
eMail:
Phone:
+421 918 674 296, +421 259 325 296
Availability:

Citations

  • Total citations       363
M. Ferrero-Jaurieta – Z. Takáč – J. Fernandez – Ľ. Horanská – G. P. Dimuro – S. Montes – H. Bustince – I. Diaz: VCI-LSTM: Vector Choquet Integral-Based Long Short-Term Memory. IEEE Transactions on Fuzzy Systems, no. 7, vol. 31, pp. 2238–2250, 2023.
  • Number of citations       1
  • Józefiak, T. – Okolewski, A. – Kaluszka, M.: On an extension of the Choquet integral for multi-valued data. Fuzzy Sets and Systems, no. 108761, vol. 474, 2024.
M. Ferrero-Jaurieta – Ľ. Horanská – J. Lafuente – R. Mesiar – G. P. Dimuro – Z. Takáč – M. Goméz – J. Fernandez – H. Bustince: Degree of totalness: How to choose the best admissible permutation for vector fuzzy integration. Fuzzy Sets and Systems, vol. 466, 2023.
  • Number of citations       2
  • Marek Kaluszka – Andrzej Okolewski – Tomasz Józefiak – Michał Boczek: On the monotonicity of the discrete Choquet-like operators. International Journal of Approximate Reasoning, pp. 109045, 2023.
  • Józefiak, T. – Kaluszka, M. – Okolewski, A.: On an extension of the Choquet integral for multi-valued data. Fuzzy Sets and Systems, no. 108761, vol. 474, 2024.
J. Fumanal – Z. Takáč – Ľ. Horanská – T. Asmus – G. P. Dimuro – C. Vidaurre – J. Fernandez – H. Bustince: A generalization of the Sugeno integral to aggregate interval-valued data: An application to brain computer interface and social network analysis. Fuzzy Sets and Systems, vol. 451, pp. 320–341, 2022.
  • Number of citations       3
  • Yifan Zhao – Hua-Wen Liu: Interval R-Sheffer Strokes and interval fuzzy Sheffer Strokes endowed with admissible orders. International Journal of Approximate Reasoning, pp. 109120, 2024.
  • Hundertmark, Sophie – Portmann, Edy: Fuzzy Conversational Character Computing. In Proceeding of AGOP 2023, Palma, 2023.
  • Gleb Beliakov – Jian-Zhang Wu – Weiping Ding: Representation, optimization and generation of fuzzy measures. Information Fusion, vol. 106, pp. 102295, 2024.
A. Saranti – M. Hudec – E. Mináriková – Z. Takáč – U. Großschedl – C. Koch – B. Pfeifer – A. Angerschmid – A. Holzinger: Actionable Explainable AI (AxAI): A Practical Example with Aggregation Functions for Adaptive Classification and Textual Explanations for Interpretable Machine Learning. Machine Learning and Knowledge Extraction, vol. 4, pp. 924–953, 2022.
  • Number of citations       9
  • de Santana, V.F. – Fucs, A. – Segura, V. – de Moraes, D.B. – Cerqueira, R.: Predicting the need for XAI from high-granularity interaction data. International Journal of Human Computer Studies, no. 103029, vol. 175, 2023.
  • Sovrano, F. – Vitali, F.: An objective metric for Explainable AI: How and why to estimate the degree of explainability. Knowledge-Based Systems, no. 110866, vol. 278, 2023.
  • Lin, R. – Du, S. – Wang, S. – Guo, W.: Consistent graph embedding network with optimal transport for incomplete multi-view clustering. Information Sciences, no. 119418, vol. 647, 2023.
  • Auletta, F. – Kallen, R.W. – di Bernardo, M. – Richardson, M.J.: Predicting and understanding human action decisions during skillful joint-action using supervised machine learning and explainable-AI. Scientific Reports, no. 1, vol. 13, 2023.
  • Triana-Martinez, J.C. – Gil-González, J. – Fernandez-Gallego, J.A. – Álvarez-Meza, A.M. – Castellanos-Dominguez, C.G.: Chained Deep Learning Using Generalized Cross-Entropy for Multiple Annotators Classification. Sensors, no. 7, vol. 23, 2023.
  • Alangari, N. – Menai, M.E.B. – Mathkour, H. – Almosallam, I.: Intrinsically Interpretable Gaussian Mixture Model. Information (Switzerland), no. 3, vol. 14, 2023.
  • Geyda, A.: Measures of Information Use Quality for Changing Activity Success in Agricultural Systems. Lecture Notes in Networks and Systems, vol. 705 LNNS, pp. 223-232, 2023.
  • Endsley, M.R.: Ironies of artificial intelligence. Ergonomics, 2023.
  • Geyda, A.S.: The method of information use schematization. In Proceedings of SPIE - The International Society for Optical Engineering, 2023.
L. De Miguel – R. H. N. Santiago – C. Wagner – J. Garibaldi – Z. Takáč – A. F. Roldán López de Hierro – H. Bustince: Extension of Restricted Equivalence Functions and Similarity Measures for Type-2 Fuzzy Sets. IEEE Transactions on Fuzzy Systems, no. 9, vol. 30, pp. 4005–4016, 2022.
  • Number of citations       4
  • Dai, J. – Wang, Z. – Huang, W.: Interval-valued fuzzy discernibility pair approach for attribute reduction in incomplete interval-valued information systems. Information Sciences, no. 119215, vol. 642, 2023.
  • Qiao, J.: Restricted equivalence functions induced from fuzzy implication functions. Iranian Journal of Fuzzy Systems, no. 2, vol. 20, pp. 151-160, 2023.
  • Jia, Z. – Qiao, J.: Extension operators for type-2 fuzzy sets derived from overlap functions. Fuzzy Sets and Systems, vol. 451, pp. 130-156, 2022.
  • Narayanan, K.B.B. – Muthusamy, S.: Prediction of machinability parameters in turning operation using interval type-2 fuzzy logic system based on semi-elliptic and trapezoidal membership functions. Soft Computing, no. 7, vol. 26, pp. 3197-3216, 2022.
J. Fumanal – Z. Takáč – J. Fernandez – J. A. Sanz – H. Goyena – C. Lin – Y. Wang – H. Bustince: Interval-Valued Aggregation Functions Based on Moderate Deviations Applied to Motor-Imagery-Based Brain–Computer Interface. IEEE Transactions on Fuzzy Systems, pp. 2706–2720, 2022.
  • Number of citations       5
  • Ng, H.W. – Guan, C.: Deep Unsupervised Representation Learning for Feature-Informed EEG Domain Extraction. IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 31, pp. 4882-4894, 2023.
  • Choi, H. – Park, J. – Yang, Y.-M.: Whitening Technique Based on Gram–Schmidt Orthogonalization for Motor Imagery Classification of Brain–Computer Interface Applications. Sensors, no. 16, vol. 22, 2022.
  • Choi, H. – Park, J. – Yang, Y.-M.: Whitening Technique Based on Gram–Schmidt Orthogonalization for Motor Imagery Classification of Brain–Computer Interface Applications. Sensors, no. 16, vol. 22, 2022.
  • Merino, L. – Navarro, G. – Santos, E.: Induced operators on bounded lattices. Information Sciences, vol. 608, pp. 114-136, 2022.
  • Xie, P. – Wang, Z. – Li, Z. – Wang, Y. – Wang, N. – Liang, Z. – Wang, J. – Chen, X.: Research on Rehabilitation Training Strategies Using Multimodal Virtual Scene Stimulation. Frontiers in Aging Neuroscience, no. 892178, vol. 14, 2022.
Z. Takáč – M. Ferrero-Jaurieta – Ľ. Horanská – N. Krivoňáková – G. P. Dimuro – H. Bustince: Enhancing LSTM for sequential image classification by modifying data aggregation. In 2021 International Conference on Electrical, Computer and Energy Technologies (ICECET), pp. 1–6, 2021.
  • Number of citations       1
  • Guang, Yang – Chao, Su-Ya – Min, Nie – Liu, Yuan-Hua – Zhang, Mei-Ling: Construction method of hybrid quantum long-short termmemory neural network for image classification br. Acta Physica Sinica, no. 5, vol. 72, 2023.
N. Krivoňáková – A. Šoltýsová – M. Tamáš – Z. Takáč – J. Krahulec – A. Ficek – M. Gál – M. Gall – M. Fehér – A. Krivjanská – I. Horáková – N. Belišová – A. Butor Škulcová – P. Bímová – T. Mackuľak: Mathematical modeling based on RT‑qPCR analysis of SARS‑CoV‑2 in wastewater as a tool for epidemiology. Scientific Reports, no. art. no. 19456, vol. 11, pp. 1–10, 2021.
  • Number of citations       16
  • Kilaru, Pruthvi – Hill, Dustin – Anderson, Kathryn – Collins, Mary B. – Green, Hyatt – Kmush, Brittany L. – Larsen, David A.: Wastewater Surveillance for Infectious Disease: A Systematic Review. American Journal of Epidemiology, 2022.
  • Lin, T. – Karthikeyan, S. – Satterlund, A. – Schooley, R. – Knight, R. – De Gruttola, V. – Martin, N. – Zou, J.: Optimizing campus-wide COVID-19 test notifications with interpretable wastewater time-series features using machine learning models. Scientific Reports, no. 1, vol. 13, 2023.
  • Acosta, N. – Dai, X. – Bautista, M.A. – Waddell, B.J. – Lee, J. – Du, K. – McCalder, J. – Pradhan, P. – Papparis, C. – Lu, X. – Chekouo, T. – Krusina, A. – Southern, D. – Williamson, T. – Clark, R.G. – Patterson, R.A. – Westlund, P. – Meddings, J. – Ruecker, N. – Lammiman, C. – Duerr, C. – Achari, G. – Hrudey, S.E. – Lee, B.E. – Pang, X. – Frankowski, K. – Hubert, C.R.J. – Parkins, M.D.: Wastewater-based surveillance can be used to model COVID-19-associated workforce absenteeism. Science of the Total Environment, no. 165172, vol. 900, 2023.
  • Torabi, F. – Li, G. – Mole, C. – Nicholson, G. – Rowlingson, B. – Smith, C.R. – Jersakova, R. – Diggle, P.J. – Blangiardo, M.: Wastewater-based surveillance models for COVID-19: A focused review on spatio-temporal models. Heliyon, no. 11, vol. 9, 2023.
  • Phan, T. – Brozak, S. – Pell, B. – Oghuan, J. – Gitter, A. – Hu, T. – Ribeiro, R.M. – Ke, R. – Mena, K.D. – Perelson, A.S. – Kuang, Y. – Wu, F.: Making waves: Integrating wastewater surveillance with dynamic modeling to track and predict viral outbreaks. Water Research, no. 120372, vol. 243, 2023.
  • Mattei, M. – Pintó, R.M. – Guix, S. – Bosch, A. – Arenas, A.: Analysis of SARS-CoV-2 in wastewater for prevalence estimation and investigating clinical diagnostic test biases. Water Research, no. 120223, vol. 242, 2023.
  • Polcz, P. – Tornai, K. – Juhász, J. – Cserey, G. – Surján, G. – Pándics, T. – Róka, E. – Vargha, M. – Reguly, I.Z. – Csikász-Nagy, A. – Pongor, S. – Szederkényi, G.: Wastewater-based modeling, reconstruction, and prediction for COVID-19 outbreaks in Hungary caused by highly immune evasive variants. Water Research, no. 120098, vol. 241, 2023.
  • Belmonte-Lopes, R. – Barquilha, C.E.R. – Kozak, C. – Barcellos, D.S. – Leite, B.Z. – da Costa, F.J.O.G. – Martins, W.L. – Oliveira, P.E. – Pereira, E.H.R.A. – Filho, C.R.M. – de Souza, E.M. – Possetti, G.R.C. – Vicente, V.A. – Etchepare, R.G.: 20-Month monitoring of SARS-CoV-2 in wastewater of Curitiba, in Southern Brazil. Environmental Science and Pollution Research, no. 31, vol. 30, pp. 76687-76701, 2023.
  • Ciannella, S. – González-Fernández, C. – Gomez-Pastora, J.: Recent progress on wastewater-based epidemiology for COVID-19 surveillance: A systematic review of analytical procedures and epidemiological modeling. Science of the Total Environment, no. 162953, vol. 878, 2023.
  • Kilaru, P. – Hill, D. – Anderson, K. – Collins, M.B. – Green, H. – Kmush, B.L. – Larsen, D.A.: Wastewater Surveillance for Infectious Disease: A Systematic Review. American Journal of Epidemiology, no. 2, vol. 192, pp. 305-322, 2023.
  • Phan, T. – Brozak, S. – Pell, B. – Gitter, A. – Xiao, A. – Mena, K.D. – Kuang, Y. – Wu, F.: A simple SEIR-V model to estimate COVID-19 prevalence and predict SARS-CoV-2 transmission using wastewater-based surveillance data. Science of the Total Environment, no. 159326, vol. 857, 2023.
  • Hopkins, L. – Persse, D. – Caton, K. – Ensor, K. – Schneider, R. – McCall, C. – Stadler, L.B.: Citywide wastewater SARS-CoV-2 levels strongly correlated with multiple disease surveillance indicators and outcomes over three COVID-19 waves. Science of the Total Environment, no. 158967, vol. 855, 2023.
  • Sridhar, J. – Parit, R. – Boopalakrishnan, G. – Rexliene, M.J. – Praveen, R. – Viswananathan, B.: Importance of wastewater-based epidemiology for detecting and monitoring SARS-CoV-2. Case Studies in Chemical and Environmental Engineering, no. 100241, vol. 6, 2022.
  • Reynolds, L.J. – Gonzalez, G. – Sala-Comorera, L. – Martin, N.A. – Byrne, A. – Fennema, S. – Holohan, N. – Kuntamukkula, S.R. – Sarwar, N. – Nolan, T.M. – Stephens, J.H. – Whitty, M. – Bennett, C. – Luu, Q. – Morley, U. – Yandle, Z. – Dean, J. – Joyce, E. – O\\\'Sullivan, J.J. – Cuddihy, J.M. – McIntyre, A.M. – Robinson, E.P. – Dahly, D. – Fletcher, N.F. – Carr, M. – De Gascun, C. – Meijer, W.G.: SARS-CoV-2 variant trends in Ireland: Wastewater-based epidemiology and clinical surveillance. Science of the Total Environment, no. 155828, vol. 838, 2022.
  • Xiao, A. – Wu, F. – Bushman, M. – Zhang, J. – Imakaev, M. – Chai, P.R. – Duvallet, C. – Endo, N. – Erickson, T.B. – Armas, F. – Arnold, B. – Chen, H. – Chandra, F. – Ghaeli, N. – Gu, X. – Hanage, W.P. – Lee, W.L. – Matus, M. – McElroy, K.A. – Moniz, K. – Rhode, S.F. – Thompson, J. – Alm, E.J.: Metrics to relate COVID-19 wastewater data to clinical testing dynamics. Water Research, no. 118070, vol. 212, 2022.
  • Cluzel, N. – Courbariaux, M. – Wang, S. – Moulin, L. – Wurtzer, S. – Bertrand, I. – Laurent, K. – Monfort, P. – Gantzer, C. – Guyader, S.L. – Boni, M. – Mouchel, J.-M. – Maréchal, V. – Nuel, G. – Maday, Y.: A nationwide indicator to smooth and normalize heterogeneous SARS-CoV-2 RNA data in wastewater. Environment International, no. 106998, vol. 158, 2022.
K. Vizárová – I. Vajová – N. Krivoňáková – R. Tiňo – Z. Takáč – Š. Vodný – S. Katuščák: Regression Analysis of Orthogonal, Cylindrical and Multivariable Color Parameters for Colorimetric Surface pH Measurement of Materials. Molecules, no. 12, vol. 26, pp. 1–9, 2021.
  • Number of citations       1
  • Rahmat, Sofiah – Altowayti, Wahid Ali Hamood – Othman, Norzila – Asharuddin, Syazwani Mohd – Saeed, Faisal – Basurra, Shadi – Eisa, Taiseer Abdalla Elfadil – Shahir, Shafinaz: Prediction of Wastewater Treatment Plant Performance Using Multivariate Statistical Analysis: A Case Study of a Regional Sewage Treatment Plant in Melaka, Malaysia. Water, no. 20, vol. 14, 2022.
I. Vajová – K. Vizárová – R. Tiňo – N. Krivoňáková – Z. Takáč – S. Katuščák: Determination of pH distribution through pH-related properties in deacidified model paper. The European Physical Journal Plus, no. 5, vol. 136, pp. 1–8, 2021.
  • Number of citations       4
  • Rahmat, Sofiah – Altowayti, Wahid Ali Hamood – Othman, Norzila – Asharuddin, Syazwani Mohd – Saeed, Faisal – Basurra, Shadi – Eisa, Taiseer Abdalla Elfadil – Shahir, Shafinaz: Prediction of Wastewater Treatment Plant Performance Using Multivariate Statistical Analysis: A Case Study of a Regional Sewage Treatment Plant in Melaka, Malaysia. Water, no. 20, vol. 14, 2022.
  • Ivanova, S. – Vesnina, A. – Fotina, N. – Prosekov, A.: Influence of Coal Mining Activities on Soil\\\'s Agrochemical and Biochemical Properties. Qubahan Academic Journal, no. 4, vol. 3, pp. 387-399, 2023.
  • Jablonský, M. – Šima, J.: The role of magnesium species in paper deacidification. A review. Journal of Cultural Heritage, vol. 61, pp. 194-200, 2023.
  • Liu, N. – Chu, D. – Chen, X. – Fu, P. – Xing, H. – Chao, X. – Luo, Y. – Mai, B. – Li, Y.: A Spray-On Microemulsion with Mold-Proof Effect on Paper. Coatings, no. 4, vol. 13, 2023.
H. Bustince – R. Mesiar – J. Fernandez – M. Galar – D. Paternain – A. H. Altalhi – G. P. Dimuro – B. Bedregal – Z. Takáč: d-Choquet integrals: Choquet integrals based on dissimilarities. Fuzzy Sets and Systems, vol. 414, pp. 1–27, 2021.
  • Number of citations       15
  • Boczek, Michal – Halcinova, Lenka – Hutnik, Ondrej – Kaluszka,\\n Marek: Novel survival functions based on conditional aggregation operators. Information Sciences, vol. 580, pp. 705-719, 2021.
  • Maleki, N. – Gholamian, M.R. – Yaghoubi, S.: An Integrated Model of BWM and Choquet Integral for Determining Fuzzy Measures in Interacting Criteria. International Journal of Information Technology and Decision Making, no. 3, vol. 21, pp. 1061-1086, 2022.
  • Khatskevich, V.L.: Means of Fuzzy Numbers in the Fuzzy Information Evaluation Problem. Automation and Remote Control, no. 3, vol. 83, pp. 407-416, 2022.
  • Karczmarek, P. – Powroznik, P. – Skublewska-Paszkowska, M. – Przylucki, S. – Lukasik, E.: Analysis of Sub-Integral Functions in the Aggregation of Classification Results Using Generalizations of the Choquet Integral on the Example of Emotion Classification. In IEEE International Conference on Fuzzy Systems, 2022.
  • Karczmarek, P. – Dolecki, M. – Powroznik, P. – Galka, L. – Pedrycz, W. – Czerwinski, D.: Quadrature-Inspired Generalized Choquet Integral. In IEEE International Conference on Fuzzy Systems, 2022.
  • Boczek, M. – Hutník, O. – Kaluszka, M.: Choquet-Sugeno-like operator based on relation and conditional aggregation operators. Information Sciences, vol. 582, pp. 1-21, 2022.
  • Boczek, M. – Józefiak, T. – Kaluszka, M. – Okolewski, A.: On the monotonicity of the discrete Choquet-like operators. International Journal of Approximate Reasoning, no. 109045, vol. 163, 2023.
  • Narukawa, Y. – Taha, M. – Torra, V.: On the definition of probabilistic metric spaces by means of fuzzy measures. Fuzzy Sets and Systems, no. 108528, vol. 465, 2023.
  • Karabacak, M.: Interval neutrosophic multi-criteria group decision-making based on Aczel–Alsina aggregation operators. Computational and Applied Mathematics, no. 3, vol. 42, 2023.
  • Boczek, M. – Kaluszka, M.: On the extended Choquet-Sugeno-like operator. International Journal of Approximate Reasoning, vol. 154, pp. 48-55, 2023.
  • Skublewska-Paszkowska, M. – Karczmarek, P. – Powroznik, P. – Lukasik, E. – Smolka, J. – Dolecki, M.: Aggregation of Tennis Multivariate Time-Series Using the Choquet Integral and Its Generalizations. In IEEE International Conference on Fuzzy Systems, 2023.
  • Karczmarek, P. – Dolecki, M. – Galka, L. – Pedrycz, W. – Czerwinski, D.: Smooth Quadrature-Inspired Generalized Choquet Integral in an Application to Anomaly Detection. In IEEE International Conference on Fuzzy Systems, 2023.
  • Karczmarek, P. – Dolecki, M. – Powroznik, P. – Lagodowski, Z.A. – Gregosiewicz, A. – Galka, L. – Pedrycz, W. – Czerwinski, D. – Jonak, K.: Quadrature-Inspired Generalized Choquet Integral in an Application to Classification Problems. IEEE Access, vol. 11, pp. 124676-124689, 2023.
  • Torra, V.: Optimal Transport and the Wasserstein Distance for Fuzzy Measures: An Example. Lecture Notes in Networks and Systems, vol. 758 LNNS, pp. 39-44, 2023.
  • Song, H. – Gong, Z. – Forrest, J.Y.-L. – Guo, W. – Herrera-Viedma, E.: Social network utility consensus model with empathic and fuzzy interactions. Computers and Industrial Engineering, no. 108904, vol. 175, 2023.
M. Sesma-Sara – R. Mesiar – J. Fernandez – Z. Takáč – H. Bustince: A proposal of the notions of ordered and strengthened ordered directional monotonicity for interval-valued functions based on admissible orders. In 2020 IEEE International Conference on Fuzzy Systems, IEEE, pp. 1–7, 2020.
  • Number of citations       2
  • Wan, R.: Monotonicity formula on cigar soliton. In Journal of Physics: Conference Series, 2021.
  • Wang, Y. – Hu, B.Q.: On interval-valued pre-(quasi-)overlap functions. Information Sciences, vol. 606, pp. 945-967, 2022.
H. Bustince – C. Marco-Detchart – J. Fernandez – C. Wagner – J. Garibaldi – Z. Takáč: Similarity between interval-valued fuzzy sets taking into account the width of the intervals and admissible orders. Fuzzy Sets and Systems, vol. 390, pp. 23–47, 2020.
  • Number of citations       32
  • Díaz, S. – Díaz, I. – Montes, S.: An interval-valued divergence for interval-valued fuzzy sets. Communications in Computer and Information Science, vol. 1238 CCIS, pp. 241-249, 2020.
  • L. T. Kóczy – M. E. Cornejo – J. Medina: Algebraic structure of fuzzy signatures. Fuzzy Sets and Systems, 2020.
  • Pekala, B. – Rak, E. – Kosior, D. – Mrukowicz, M. – Bazan, J.G.: Application of similarity measures with uncertainty in classification methods. In IEEE International Conference on Fuzzy Systems, 2020.
  • Wu, H. – Wang, J. – Liu, S. – Yang, T.: Research on decision-making of emergency plan for waterlogging disaster in subway station project based on linguistic intuitionistic fuzzy set and TOPSIS. Mathematical Biosciences and Engineering, no. 5, vol. 17, pp. 4825-4851, 2020.
  • Koczy, Laszlo T. – Cornejo, M. Eugenia – Medina, Jesus: Algebraic structure of fuzzy signatures. Fuzzy Sets and Systems, no. SI, vol. 418, pp. 25-50, 2021.
  • Guijarro, E. – Babiloni, E. – Canós-Darós, M.J. – Canós-Darós, L. – Estellés-Miguel, S.: Fuzzy Modeling Approach to On-Hand Stock Levels Estimation in (R,S) Inventory Systems with Lost Sales. International Journal of Industrial Engineering and Management, no. 3, vol. 13, pp. 464-474, 2020.
  • Jia, Qianlei – Hu, Jiayue – Safwat, Ehab – Kamel, Ahmed: Polar coordinate system to solve an uncertain linguistic Z-number and\\n its application in multicriteria group decision-making. Engineering Applications of Artificial Intelligence, no. 104437, vol. 105, 2021.
  • Suo, C. – Li, Y. – Li, Z.: On n-polygonal interval-value fuzzy sets and numbers. Fuzzy Sets and Systems, 2020.
  • Diaz-Vazquez, Susana – Torres-Manzanera, Emilio – Diaz, Irene and\\n Montes, Susana: On the Search for a Measure to Compare Interval-Valued Fuzzy Sets. Mathematics, no. 24, vol. 9, 2021.
  • Li, X. – Suo, C. – Li, Y.: Width-based distance measures on interval-valued intuitionistic fuzzy sets. Journal of Intelligent and Fuzzy Systems, no. 5, vol. 40, pp. 8857-8869, 2021.
  • Cheng, Xianjuan – Wan, Shuping – Dong, Jiuying – Martinez, Luis: New decision-making methods with interval reciprocal preference\\n relations: A new admissible order relation of intervals. Information Sciences, vol. 569, pp. 400-429, 2021.
  • Suo, Chunfeng – Li, Yongming – Li, Zhihui: On n-polygonal interval-valued fuzzy sets. Fuzzy Sets and Systems, no. SI, vol. 417, pp. 46-70, 2021.
  • Che, Renqing – Suo, Chunfeng – Li, Yongming: An approach to construct entropies on interval-valued intuitionistic\\n fuzzy sets by their distance functions. Soft Computing, no. 10, vol. 25, pp. 6879-6889, 2021.
  • Pekala, Barbara – Dyczkowski, Krzysztof – Grzegorzewski, Przemyslaw\\n – Bentkowska, Urszula: Inclusion and similarity measures for interval-valued fuzzy sets based\\n on aggregation and uncertainty assessment. Information Sciences, vol. 547, pp. 1182-1200, 2021.
  • Pekala, Barbara – Kosior, Dawid – Dyczkowski, Krzysztof – Szkola,\\n Jaroslaw: Application of entropy measures with uncertainty in classification\\n methods with missing data problem. In IEEE Cis International Conference on Fuzzy Systems 2021 (fuzz-IEEE), 2021.
  • Pekala, Barbara – Dyczkowski, Krzysztof – Szkola, Jaroslaw and\\n Kosior, Dawid: Classification of uncertain data with a selection of relevant features\\n based on similarities measures of Interval-Valued Fuzzy Sets. In IEEE Cis International Conference on Fuzzy Systems 2021 (fuzz-IEEE), 2021.
  • Moura, B.M.P. – Schneider, G.B. – Yamin, A.C. – Santos, H. – Reiser, R.H.S. – Bedregal, B.: Interval-valued Fuzzy Logic approach for overloaded hosts in consolidation of virtual machines in cloud computing. Fuzzy Sets and Systems, vol. 446, pp. 144-166, 2022.
  • Petry, F.E. – Yager, R.R.: Interval-valued fuzzy sets aggregation and evaluation approaches. Applied Soft Computing, no. 108887, vol. 124, 2022.
  • Pan, L. – Gao, X. – Deng, Y. – Cheong, K.H.: Constrained Pythagorean Fuzzy Sets and Its Similarity Measure. IEEE Transactions on Fuzzy Systems, no. 4, vol. 30, pp. 1102-1113, 2022.
  • Sayed, O.R. – Sayed, N.H. – Hassan, N.: Lower interval-valued intuitionistic fuzzy separation axioms. Journal of Prime Research in Mathematics, no. 1, vol. 18, pp. 83-95, 2022.
  • Pękala, B. – Dyczkowski, K. – Szkoła, J. – Kosior, D.: Selection of Relevant Features Based on Optimistic and Pessimistic Similarities Measures of Interval-Valued Fuzzy Sets. Communications in Computer and Information Science, vol. 1601 CCIS, pp. 307-319, 2022.
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  • Kosior, D. – PÈ©kala, B.: Influence of Interval-Valued Measures on Classification Methods with Missing Values. Lecture Notes in Networks and Systems, vol. 338 LNNS, pp. 15-27, 2022.
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Z. Takáč: MRP Tasks, Critical Thinking and Intrinsic Motivation to Proving. Teaching Mathematics and Computer Science, no. 1, vol. 8, pp. 149–168, 2010.
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Z. Takáč: On the motivation to reasoning and proving in mathematics (in Czech). Pokroky matematiky, fyziky a astronómie, no. 3, vol. 54, pp. 243–251, 2009.
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