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Directional monotonicity of multidimensional fusion functions with respect to admissible orders. (English) Zbl 1543.26006

Summary: The notion of directional monotonicity emerged as a relaxation of the monotonicity condition of aggregation functions. As the extension of aggregation functions to fuse more complex information than numeric data, directional monotonicity was extended to the framework of multidimensional data, with respect to the product order, which is a partial order. In this work, we present the notion of admissible order for multidimensional data and we define the concept of directional monotonicity for multidimensional fusion functions with respect to an admissible order. Moreover, we study the main properties of directionally monotone functions in this new context. We conclude that, while some of the properties are still valid (e.g. the set of directions of increasingness is still closed under convex combinations), some of the main ones no longer hold (e.g. there does not exist a finite set of directions that characterize standard monotonicity in terms of directional monotonicity).

MSC:

26E50 Fuzzy real analysis
26A48 Monotonic functions, generalizations
Full Text: DOI

References:

[1] Beliakov, G.; Bustince, H.; Calvo, T., A Practical Guide to Averaging Functions, Studies in Fuzziness and Soft Computing (2016), Springer International Publishing
[2] Beliakov, G.; Calvo, T.; Wilkin, T., Three types of monotonicity of averaging functions, Knowl.-Based Syst., 72, 114-122 (2014)
[3] Beliakov, G.; James, S.; Kolesárová, A.; Mesiar, R., Cardinality-limiting extended pre-aggregation functions, Inf. Fusion, 76, 66-74 (2021)
[4] Bellet, A.; Habrard, A.; Sebban, M., A survey on metric learning for feature vectors and structured data (2013), arXiv preprint
[5] Bullen, P. S., Handbook of Means and Their Inequalities, vol. 560 (2013), Springer Science & Business Media
[6] Bustince, H.; Barrenechea, E.; Sesma-Sara, M.; Lafuente, J.; Dimuro, G. P.; Mesiar, R.; Kolesárová, A., Ordered directionally monotone functions. Justification and application, IEEE Trans. Fuzzy Syst., 26, 4, 2237-2250 (2018)
[7] Bustince, H.; Fernández, J.; Kolesárová, A.; Mesiar, R., Generation of linear orders for intervals by means of aggregation functions, Fuzzy Sets Syst., 220, 69-77 (2013) · Zbl 1284.03242
[8] Bustince, H.; Fernandez, J.; Kolesárová, A.; Mesiar, R., Directional monotonicity of fusion functions, Eur. J. Oper. Res., 244, 1, 300-308 (2015) · Zbl 1346.26004
[9] Bustince, H.; Galar, M.; Bedregal, B.; Kolesarova, A.; Mesiar, R., A new approach to interval-valued Choquet integrals and the problem of ordering in interval-valued fuzzy set applications, IEEE Trans. Fuzzy Syst., 21, 6, 1150-1162 (2013)
[10] Bustince, H.; Mesiar, R.; Kolesárová, A.; Dimuro, G.; Fernandez, J.; Diaz, I.; Montes, S., On some classes of directionally monotone functions, Fuzzy Sets Syst., 386, 161-178 (2020) · Zbl 1465.26022
[11] Calvo, T.; Kolesárová, A.; Komorníková, M.; Mesiar, R., A Review of Aggregation Operators (2001), University of Alcala Press: University of Alcala Press Alcala de Henares
[12] Cox, D.; Battey, H., Large numbers of explanatory variables, a semi-descriptive analysis, Proc. Natl. Acad. Sci., 114, 32, 8592-8595 (2017) · Zbl 1407.62399
[13] De Baets, B.; De Meyer, H., Maximal directions of monotonicity of an aggregation function, Fuzzy Sets Syst., 433, 54-78 (2022) · Zbl 1522.62028
[14] De Baets, B.; Mesiar, R., Triangular norms on product lattices, Fuzzy Sets Syst., 104, 1, 61-75 (1999) · Zbl 0935.03060
[15] De Miguel, L.; Sesma-Sara, M.; Elkano, M.; Asiain, M.; Bustince, H., An algorithm for group decision making using n-dimensional fuzzy sets, admissible orders and OWA operators, Inf. Fusion, 37, 126-131 (2017)
[16] Demirci, M., Aggregation operators on partially ordered sets and their categorical foundations, Kybernetika, 42, 3, 261-277 (2006) · Zbl 1249.03091
[17] Deschrijver, G.; Cornelis, C., Representability in interval-valued fuzzy set theory, Int. J. Uncertain. Fuzziness Knowl.-Based Syst., 15, 3, 345-361 (2007) · Zbl 1144.03033
[18] Dimuro, G. P.; Bustince, H.; Fernandez, J.; Mesiar, R.; Bedregal, B., New results on pre-aggregation functions: introducing (light) pre-t-norms, (2017 Joint 17th World Congress of International Fuzzy Systems Association and 9th International Conference on Soft Computing and Intelligent Systems (IFSA-SCIS) (2017), IEEE)
[19] Dimuro, G. P.; Bustince, H.; Fernandez, J.; Sanz, J. A.; Lucca, G.; Bedregal, B., On the definition of the concept of pre-t-conorms, (2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) (2017), IEEE)
[20] Dimuro, G. P.; Fernández, J.; Bedregal, B.; Mesiar, R.; Sanz, J. A.; Lucca, G.; Bustince, H., The state-of-art of the generalizations of the Choquet integral: from aggregation and pre-aggregation to ordered directionally monotone functions, Inf. Fusion, 57, 27-43 (2020)
[21] Drygaś, P.; Pȩkala, B.; Balicki, K.; Kosior, D., Influence of new interval-valued pre-aggregation function on medical decision making, (2020 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) (2020), IEEE), 1-8
[22] Elkano, M.; Sanz, J. A.; Galar, M.; Pekala, B.; Bentkowska, U.; Bustince, H., Composition of interval-valued fuzzy relations using aggregation functions, Inf. Sci., 369, 690-703 (2016) · Zbl 1428.03062
[23] Fumanal-Idocin, J.; Takáč, Z.; Horanská, Ľ.; da Cruz Asmus, T.; Dimuro, G.; Vidaurre, C.; Fernandez, J.; Bustince, H., A generalization of the Sugeno integral to aggregate interval-valued data: an application to brain computer interface and social network analysis, Fuzzy Sets Syst., 451, 320-341 (2022) · Zbl 1522.28022
[24] Gagolewski, M., Data Fusion: Theory, Methods, and Applications (2015), Institute of Computer Science, Polish Academy of Sciences
[25] Gagolewski, M., Penalty-based aggregation of multidimensional data, Fuzzy Sets Syst., 325, 4-20 (2017) · Zbl 1380.68359
[26] Gagolewski, M.; Pérez-Fernández, R.; De Baets, B., An inherent difficulty in the aggregation of multidimensional data, IEEE Trans. Fuzzy Syst., 28, 3, 602-606 (2019)
[27] Grabisch, M.; Marichal, J.; Mesiar, R.; Pap, E., Aggregation Functions (2009), Cambridge University Press · Zbl 1196.00002
[28] Kolmogorov, A. N.; Castelnuovo, G., Sur la Notion de la Moyenne (1930), G. Bardi, Tip. della R. Accad. dei Lincei · JFM 56.0198.02
[29] Komorníková, M.; Mesiar, R., Aggregation functions on bounded partially ordered sets and their classification, Fuzzy Sets Syst., 175, 1, 48-56 (2011) · Zbl 1253.06004
[30] Levy, O.; Goldberg, Y., Dependency-based word embeddings, (Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers) (2014)), 302-308
[31] Lucca, G.; Sanz, J.; Dimuro, G.; Bedregal, B.; Asiain, M. J.; Elkano, M.; CC-integrals, H. Bustince, Choquet-like copula-based aggregation functions and its application in fuzzy rule-based classification systems, Knowl.-Based Syst., 119, 32-43 (2017)
[32] Lucca, G.; Sanz, J. A.; Dimuro, G. P.; Bedregal, B.; Bustince, H.; Mesiar, R., CF-integrals: a new family of pre-aggregation functions with application to fuzzy rule-based classification systems, Inf. Sci., 435, 94-110 (2018) · Zbl 1440.68293
[33] Lucca, G.; Sanz, J. A.; Dimuro, G. P.; Bedregal, B.; Mesiar, R.; Kolesárová, A.; Bustince, H., Preaggregation functions: construction and an application, IEEE Trans. Fuzzy Syst., 24, 2, 260-272 (2016)
[34] Marco-Detchart, C.; Lucca, G.; Lopez-Molina, C.; Miguel, L. D.; Dimuro, G. P.; Bustince, H., Neuro-inspired edge feature fusion using Choquet integrals, Inf. Sci., 581, 740-754 (2021) · Zbl 1535.68440
[35] Mesiar, R.; Kolesárová, A.; Stupňanová, A., Quo vadis aggregation?, Int. J. Gen. Syst., 47, 2, 97-117 (2018)
[36] Mesiar, R.; Pap, E., Aggregation of infinite sequences, Inf. Sci., 178, 18, 3557-3564 (2008) · Zbl 1142.40300
[37] Pérez-Fernández, R., On an order-based multivariate median, Fuzzy Sets Syst., 414, 70-84 (2021) · Zbl 1467.62082
[38] Pérez-Fernández, R.; De Baets, B.; Gagolewski, M., A taxonomy of monotonicity properties for the aggregation of multidimensional data, Inf. Fusion, 52, 322-334 (2019)
[39] Qiao, J.; Gong, Z., On \(\overrightarrow{r} \)-(quasi-)overlap functions, IEEE Trans. Fuzzy Syst., 29, 10, 3178-3185 (2021)
[40] Sesma-Sara, M.; Bustince, H.; Barrenechea, E.; Lafuente, J.; Kolesárová, A.; Mesiar, R., Edge detection based on ordered directionally monotone functions, (Advances in Fuzzy Logic and Technology 2017 (2017), Springer), 301-307
[41] Sesma-Sara, M.; De Miguel, L.; Mesiar, R.; Fernandez, J.; Bustince, H., Interval-valued pre-aggregation functions: a study of directional monotonicity or interval-valued functions, (2019 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) (2019), IEEE), 1-6
[42] Sesma-Sara, M.; De Miguel, L.; Roldán López de Hierro, A. F.; Lafuente, J.; Mesiar, R.; Bustince, H., Pointwise directional increasingness and geometric interpretation of directionally monotone functions, Inf. Sci., 501, 236-247 (2019) · Zbl 1453.68185
[43] Sesma-Sara, M.; Lafuente, J.; Roldán, A.; Mesiar, R.; Bustince, H., Strengthened ordered directionally monotone functions. Links between the different notions of monotonicity, Fuzzy Sets Syst., 357, 151-172 (2019) · Zbl 1423.26057
[44] Sesma-Sara, M.; Mesiar, R.; Bustince, H., Weak and directional monotonicity of functions on Riesz spaces to fuse uncertain data, Fuzzy Sets Syst., 386, 145-160 (2020) · Zbl 1465.03088
[45] Su, P.; Chen, T.; Mao, H.; Xie, J.; Zhao, Y.; Liu, J., On the application of preaggregation functions to fuzzy pattern tree, (2019 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) (2019), IEEE)
[46] Wallis, W. D.; Shoubridge, P.; Kraetz, M.; Ray, D., Graph distances using graph union, Pattern Recognit. Lett., 22, 6-7, 701-704 (2001) · Zbl 1010.68896
[47] Wang, Y.; Hu, B. Q., On interval-valued pre-(quasi-)overlap functions, Inf. Sci., 606, 945-967 (2022) · Zbl 07814180
[48] Wang, Y.; Hu, B. Q., Pre-(quasi-)overlap functions on bounded posets, Fuzzy Sets Syst., 451, 157-175 (2022) · Zbl 1522.03292
[49] Wieczynski, J.; Fumanal-Idocin, J.; Lucca, G.; Borges, E. N.; da Cruz Asmus, T.; Emmendorfer, L. R.; Bustince, H.; Dimuro, G. P., d-XC integrals: on the generalization of the expanded form of the Choquet integral by restricted dissimilarity functions and their applications, IEEE Trans. Fuzzy Syst., 30, 12, 5376-5389 (2022)
[50] Wieczynski, J.; Lucca, G.; Dimuro, G. P.; Borges, E. N.; Sanz, J. A.; da Cruz Asmus, T.; Fernandez, J.; Bustince, H., \(d C_F\)-integrals: generalizing \(C_F\)-integrals by means of restricted dissimilarity functions, IEEE Trans. Fuzzy Syst., 31, 1, 160-173 (2023)
[51] Wilkin, T.; Beliakov, G., Weakly monotonic averaging functions, Int. J. Intell. Syst., 30, 2, 144-169 (2015)
[52] Xu, Z.; Yager, R. R., Some geometric aggregation operators based on intuitionistic fuzzy sets, Int. J. Gen. Syst., 35, 4, 417-433 (2006) · Zbl 1113.54003
[53] Yang, R.; Pu, X.; Paternain, D.; Yager, R.; Mesiar, R.; Bustince, H.; Jin, L., Some methods for Yager preference involved aggregations in multi-criteria and multi-sources evaluation, Int. J. Uncertain. Fuzziness Knowl.-Based Syst., 29, 04, 587-602 (2021) · Zbl 1507.91065
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