Skip to main content
Erschienen in: Granular Computing 3/2019

20.08.2018 | Original Paper

Three-way decisions with reflexive probabilistic rough fuzzy sets

verfasst von: Jian-Min Ma, Hong-Ying Zhang, Yu-Hua Qian

Erschienen in: Granular Computing | Ausgabe 3/2019

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

The theory of three-way decisions is used to classify a set of objects into the three disjoint parts of the positive, negative and boundary regions. This paper mainly studies three-way decisions with reflexive probabilistic rough fuzzy sets. We first discuss reflexive probabilistic rough sets in a reflexive probabilistic approximation space. For any fuzzy set and a level value, reflexive probabilistic rough fuzzy sets are introduced based on a pair of thresholds and a reflexive binary relation. Related properties of them are investigated. The lower and upper reflexive probabilistic rough fuzzy approximations are monotonic when the two thresholds and the level value increase or decrease. To give the physical interpretation of the required thresholds in reflexive probabilistic rough fuzzy sets, a set of states is constructed based on any fuzzy set and a level value. Three-way classifications in reflexive probabilistic rough fuzzy sets are then discussed. This method gives the values of the pair of thresholds using the loss functions. Meanwhile, using the minimum-risk decision rules, the lower and upper reflexive probabilistic rough fuzzy sets are constructed, which are consistent with the meaning of the lower and upper approximations in rough set theory. Related algorithm and example are also shown to explain the proposed method.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Literatur
Zurück zum Zitat Dou HL, Yang XB, Song XN, Yu HL, Wu WZ, Yang JY (2016) Decision-theoretic rough set: a multicost strategy. Knowl Based Syst 91:71–83CrossRef Dou HL, Yang XB, Song XN, Yu HL, Wu WZ, Yang JY (2016) Decision-theoretic rough set: a multicost strategy. Knowl Based Syst 91:71–83CrossRef
Zurück zum Zitat Dubois D, Prade H (2007) Fuzzy rough set and rough fuzzy set. Int J Genera Syst 17(2–3):191–209MATH Dubois D, Prade H (2007) Fuzzy rough set and rough fuzzy set. Int J Genera Syst 17(2–3):191–209MATH
Zurück zum Zitat Duda RO, Hart PE (1973) Pattern classification and scene analysis. Wiley, New YorkMATH Duda RO, Hart PE (1973) Pattern classification and scene analysis. Wiley, New YorkMATH
Zurück zum Zitat Gong ZT, Sun BZ (2008) Probability rough sets model between different universes and its applications. In: International conference on machine learning and cyernetics, pp 561–565 Gong ZT, Sun BZ (2008) Probability rough sets model between different universes and its applications. In: International conference on machine learning and cyernetics, pp 561–565
Zurück zum Zitat Greco S, Matarazzo B, Slowinski R (2002) Rough approximation by dominance relations. Int J Intell Syst 17(2):153–171CrossRefMATH Greco S, Matarazzo B, Slowinski R (2002) Rough approximation by dominance relations. Int J Intell Syst 17(2):153–171CrossRefMATH
Zurück zum Zitat Herbert JP, Yao JT (2009) Criteria for choosing a rough set model. J Comput Math Appl 57:908–918CrossRefMATH Herbert JP, Yao JT (2009) Criteria for choosing a rough set model. J Comput Math Appl 57:908–918CrossRefMATH
Zurück zum Zitat Hu QH, Yu DR, Liu JF, Wu CX (2008) Neighborhood rough set based heterogeneous feature subset selection. Inf Sci 178(18):3577–3594MathSciNetCrossRefMATH Hu QH, Yu DR, Liu JF, Wu CX (2008) Neighborhood rough set based heterogeneous feature subset selection. Inf Sci 178(18):3577–3594MathSciNetCrossRefMATH
Zurück zum Zitat Huang CC, Li JH, Mei CL, Wu WZ (2017) Three-way concept learning based on cognitive operators: an information fusion viewpoint. Int J Approx Reason 83:218–242MathSciNetCrossRefMATH Huang CC, Li JH, Mei CL, Wu WZ (2017) Three-way concept learning based on cognitive operators: an information fusion viewpoint. Int J Approx Reason 83:218–242MathSciNetCrossRefMATH
Zurück zum Zitat Li M, Deng SB, Wang L, Feng S, Fan J (2014) Hierarchical clustering algorithm for categorical data using a probabilistic rough set model. Knowl Based Syst 65:60–71CrossRef Li M, Deng SB, Wang L, Feng S, Fan J (2014) Hierarchical clustering algorithm for categorical data using a probabilistic rough set model. Knowl Based Syst 65:60–71CrossRef
Zurück zum Zitat Li JH, Huang CC, Qi JJ, Qian YH, Liu WQ (2017) Three-way cognitive concept learning via multi-granularity. Inf Sci 378:244–263CrossRef Li JH, Huang CC, Qi JJ, Qian YH, Liu WQ (2017) Three-way cognitive concept learning via multi-granularity. Inf Sci 378:244–263CrossRef
Zurück zum Zitat Liang DC, Xu ZS, Liu D (2017) Three-way decisions based on decision-theoretic rough sets with dual hesitant fuzzy information. Inf Sci 396:127–143CrossRef Liang DC, Xu ZS, Liu D (2017) Three-way decisions based on decision-theoretic rough sets with dual hesitant fuzzy information. Inf Sci 396:127–143CrossRef
Zurück zum Zitat Lin TY (1988) Neighborhood systems and relational database. In: Proceedings of CSC, pp 132–155 Lin TY (1988) Neighborhood systems and relational database. In: Proceedings of CSC, pp 132–155
Zurück zum Zitat Lin TY (1989) Neighborhood systems and approximation in database and knowledge base systems. In: Proceedings of the fourth international symposium on methodologies of intelligent systems, pp 75–86 Lin TY (1989) Neighborhood systems and approximation in database and knowledge base systems. In: Proceedings of the fourth international symposium on methodologies of intelligent systems, pp 75–86
Zurück zum Zitat Liu D, Li TR, Zhang JB (2015) Incremental updating approximations in probabilistic rough sets under the variation of attributes. Knowl Based Syst 73:81–96CrossRef Liu D, Li TR, Zhang JB (2015) Incremental updating approximations in probabilistic rough sets under the variation of attributes. Knowl Based Syst 73:81–96CrossRef
Zurück zum Zitat Ma WM, Sun BZ (2012a) On relationship between probabilistic rough set and Bayesian risk decision over two universes. Int J Genera Syst 41(3):225–245MathSciNetCrossRefMATH Ma WM, Sun BZ (2012a) On relationship between probabilistic rough set and Bayesian risk decision over two universes. Int J Genera Syst 41(3):225–245MathSciNetCrossRefMATH
Zurück zum Zitat Pawlak Z (1991) Rough sets, theoretical aspects of reasoning about data. Kluwer Academic Publishers, DordrechtMATH Pawlak Z (1991) Rough sets, theoretical aspects of reasoning about data. Kluwer Academic Publishers, DordrechtMATH
Zurück zum Zitat Pawlak Z, Wong SKM, Ziarko W (1988) Rough sets: probabilistic versus deterministic approach. Int J Man Mach Stud 29:81–95CrossRefMATH Pawlak Z, Wong SKM, Ziarko W (1988) Rough sets: probabilistic versus deterministic approach. Int J Man Mach Stud 29:81–95CrossRefMATH
Zurück zum Zitat Pedrycz W, Chen SM (2011) Granular computing and intelligent systems: design with information granules of high order and high type. Springer, HeidelbergCrossRef Pedrycz W, Chen SM (2011) Granular computing and intelligent systems: design with information granules of high order and high type. Springer, HeidelbergCrossRef
Zurück zum Zitat Pedrycz W, Chen SM (2015a) Granular computing and decision-making: interactive and iterative approaches. Springer, HeidelbergCrossRef Pedrycz W, Chen SM (2015a) Granular computing and decision-making: interactive and iterative approaches. Springer, HeidelbergCrossRef
Zurück zum Zitat Pedrycz W, Chen SM (2015b) Information granularity, big data, and computational intelligence. Springer, HeidelbergCrossRef Pedrycz W, Chen SM (2015b) Information granularity, big data, and computational intelligence. Springer, HeidelbergCrossRef
Zurück zum Zitat Qian YH, Liang XY, Lin GP, Guo Q, Liang JY (2017) Local multigranulation decision-theoretic rough sets. Int J Approx Reason 82:119–137MathSciNetCrossRefMATH Qian YH, Liang XY, Lin GP, Guo Q, Liang JY (2017) Local multigranulation decision-theoretic rough sets. Int J Approx Reason 82:119–137MathSciNetCrossRefMATH
Zurück zum Zitat Sang YL, Liang JY, Qian YH (2016) Decision-theoretic rough sets under dynamic granulation. Knowl Based Syst 91:84–92CrossRef Sang YL, Liang JY, Qian YH (2016) Decision-theoretic rough sets under dynamic granulation. Knowl Based Syst 91:84–92CrossRef
Zurück zum Zitat Shen YH, Wang FX (2011) Variable precision rough set model over two universes and its properties. Soft Comput 15(3):557–567CrossRefMATH Shen YH, Wang FX (2011) Variable precision rough set model over two universes and its properties. Soft Comput 15(3):557–567CrossRefMATH
Zurück zum Zitat Skowron A, Stepaniuk J, Swiniarski R (2012) Modeling rough granular computing based on approximation spaces. Inf Sci 184:20–43CrossRefMATH Skowron A, Stepaniuk J, Swiniarski R (2012) Modeling rough granular computing based on approximation spaces. Inf Sci 184:20–43CrossRefMATH
Zurück zum Zitat Slowinski R, Vanderpooten D (2000) A generalized definition of rough approximations based on similarity. IEEE Trans Knowl Data Eng 12:331–336CrossRef Slowinski R, Vanderpooten D (2000) A generalized definition of rough approximations based on similarity. IEEE Trans Knowl Data Eng 12:331–336CrossRef
Zurück zum Zitat Sun BZ, Ma WM, Zhao HY, Wang XX (2012) Probabilistic fuzzy rough set model over two universes. Lect Notes Comput Sci 7413:83–93CrossRef Sun BZ, Ma WM, Zhao HY, Wang XX (2012) Probabilistic fuzzy rough set model over two universes. Lect Notes Comput Sci 7413:83–93CrossRef
Zurück zum Zitat Yang HL, Liao XW, Wang SY, Wang J (2013) Fuzzy probabilistic rough set model on two universes and its applications. Int J Approx Reason 54:1410–1420MathSciNetCrossRefMATH Yang HL, Liao XW, Wang SY, Wang J (2013) Fuzzy probabilistic rough set model on two universes and its applications. Int J Approx Reason 54:1410–1420MathSciNetCrossRefMATH
Zurück zum Zitat Yao YY (1998b) Relational interpretations of neighborhood operators and rough set approximation operators. Inf Sci 111(1–4):239–259MathSciNetCrossRefMATH Yao YY (1998b) Relational interpretations of neighborhood operators and rough set approximation operators. Inf Sci 111(1–4):239–259MathSciNetCrossRefMATH
Zurück zum Zitat Yao YY (1999) Rough sets, neighborhood systems and granular computing. IEEE Can Conf Electr Comput Engine 2002(3):1553–1558 Yao YY (1999) Rough sets, neighborhood systems and granular computing. IEEE Can Conf Electr Comput Engine 2002(3):1553–1558
Zurück zum Zitat Yao YY (2003) Probabilistic approaches to rough sets. Expert Syst 20:287–297CrossRef Yao YY (2003) Probabilistic approaches to rough sets. Expert Syst 20:287–297CrossRef
Zurück zum Zitat Yao YY (2008) Probabilistic rough set approximations. Int J Approx Reason 49:255–271CrossRefMATH Yao YY (2008) Probabilistic rough set approximations. Int J Approx Reason 49:255–271CrossRefMATH
Zurück zum Zitat Yao YY (2009) Three-way decision: an interpretation of rules in rough set theory. In: Wen P, Li Y, Polkowski L, Yao Y, Tsumoto H, Wang G (eds) RSKT, vol 5589. LNCS (LNAI), New York, pp 642–649 Yao YY (2009) Three-way decision: an interpretation of rules in rough set theory. In: Wen P, Li Y, Polkowski L, Yao Y, Tsumoto H, Wang G (eds) RSKT, vol 5589. LNCS (LNAI), New York, pp 642–649
Zurück zum Zitat Yao YY, Lin TY (1996) Generalization of rough sets using modal logic. Intell Autom Soft Comput 2(2):103–120CrossRef Yao YY, Lin TY (1996) Generalization of rough sets using modal logic. Intell Autom Soft Comput 2(2):103–120CrossRef
Zurück zum Zitat Yao YY, Wong SKM (1990) A decision-theoretic rough set model. In: Ras ZW, Zemankova M, Emrich ML (eds) Methodologies for intelligent systems, vol 5. North-Holland, New York, pp 17–24 Yao YY, Wong SKM (1990) A decision-theoretic rough set model. In: Ras ZW, Zemankova M, Emrich ML (eds) Methodologies for intelligent systems, vol 5. North-Holland, New York, pp 17–24
Zurück zum Zitat Yao YY, Wong SKM (1992) A decision theoretic framework for approximating concepts. Int J Man Mach Stud 37:793–809CrossRef Yao YY, Wong SKM (1992) A decision theoretic framework for approximating concepts. Int J Man Mach Stud 37:793–809CrossRef
Zurück zum Zitat Zadeh L (1998) Some reflections on soft computing, granular computing and their roles in the conception, design and utilization of information/intelligent systems. Soft Comput 2:23–25CrossRef Zadeh L (1998) Some reflections on soft computing, granular computing and their roles in the conception, design and utilization of information/intelligent systems. Soft Comput 2:23–25CrossRef
Metadaten
Titel
Three-way decisions with reflexive probabilistic rough fuzzy sets
verfasst von
Jian-Min Ma
Hong-Ying Zhang
Yu-Hua Qian
Publikationsdatum
20.08.2018
Verlag
Springer International Publishing
Erschienen in
Granular Computing / Ausgabe 3/2019
Print ISSN: 2364-4966
Elektronische ISSN: 2364-4974
DOI
https://doi.org/10.1007/s41066-018-0125-2

Weitere Artikel der Ausgabe 3/2019

Granular Computing 3/2019 Zur Ausgabe

Premium Partner