Skip to main content
Erschienen in: Granular Computing 3/2021

21.02.2020 | Original Paper

Hexagonal fuzzy number and its distinctive representation, ranking, defuzzification technique and application in production inventory management problem

verfasst von: Avishek Chakraborty, Suman Maity, Shalini Jain, Sankar Prasad Mondal, Shariful Alam

Erschienen in: Granular Computing | Ausgabe 3/2021

Einloggen

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

search-config
loading …

Abstract

In this article, we envisage the hexagonal number from various distinct rational perspectives and viewpoints to give it a look of a conundrum. Hexagonal fuzzy number is used as an authoritative logic to ease understanding of vagueness information. This article portrays an impression of different representation, ranking, defuzzification and application of hexagonal fuzzy number. Additionally, disjunctive types of linear and nonlinear hexagonal fuzzy numbers both with symmetry and asymmetry are addressed here along with its graphical representation. Further, a new ranking method is established and two different kinds of approaches to computing the defuzzification of hexagonal fuzzy number are fabricated in this research arena. Finally, one production inventory management problem has been analyzed and solved in the hexagonal fuzzy environment along with the numerical sensitivity analysis tables. This real-life problem plays a crucial role to demonstrate the effectiveness of this method compared to the usual results in crisps environment. This noble thought will help us to solve a plethora of daily-life problems in uncertainty arena.

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 Abbasbandy S, Asady B (2006) Ranking of fuzzy numbers by sign distance. Inform Sci 176:2405–2416MathSciNetMATH Abbasbandy S, Asady B (2006) Ranking of fuzzy numbers by sign distance. Inform Sci 176:2405–2416MathSciNetMATH
Zurück zum Zitat Abbasbandy S, Hajjari T (2009b) A new approach for ranking of trapezoidal fuzzy numbers. Comput Math Appl 57:413–419MathSciNetMATH Abbasbandy S, Hajjari T (2009b) A new approach for ranking of trapezoidal fuzzy numbers. Comput Math Appl 57:413–419MathSciNetMATH
Zurück zum Zitat Abbasbandy S, Hajjari T (2011) An improvement on centroid point method for ranking of fuzzy numbers. J Sci IAU 78:109–119 Abbasbandy S, Hajjari T (2011) An improvement on centroid point method for ranking of fuzzy numbers. J Sci IAU 78:109–119
Zurück zum Zitat Asady B (2010) The revised method of ranking LR fuzzy number based on deviation degree. Expert Syst Appl 37:5056–5060 Asady B (2010) The revised method of ranking LR fuzzy number based on deviation degree. Expert Syst Appl 37:5056–5060
Zurück zum Zitat Atanassov K (1986) Intuitionistic fuzzy sets. Fuzzy Sets Syst 20:87–96MATH Atanassov K (1986) Intuitionistic fuzzy sets. Fuzzy Sets Syst 20:87–96MATH
Zurück zum Zitat Castillo O, Cervantes L, Pedrycz W (2019) A new approach to control of multivariable systems through a hierarchical aggregation of fuzzy controllers. Granul Comput 4:1–13 Castillo O, Cervantes L, Pedrycz W (2019) A new approach to control of multivariable systems through a hierarchical aggregation of fuzzy controllers. Granul Comput 4:1–13
Zurück zum Zitat Chakraborty A, Broumi S, Singh PK (2019a) Some properties of pentagonal neutrosophic numbers and its applications in transportation problem environment. Neutrosophic Sets Syst 28:200–215 Chakraborty A, Broumi S, Singh PK (2019a) Some properties of pentagonal neutrosophic numbers and its applications in transportation problem environment. Neutrosophic Sets Syst 28:200–215
Zurück zum Zitat Chakraborty A, Mondal S, Broumi S (2019b) De-neutrosophication technique of pentagonal neutrosophic number and application in minimal spanning tree. Neutrosophic Sets Syst 29:1–18 Chakraborty A, Mondal S, Broumi S (2019b) De-neutrosophication technique of pentagonal neutrosophic number and application in minimal spanning tree. Neutrosophic Sets Syst 29:1–18
Zurück zum Zitat Chakraborty A, Mondal SP, Alam S, Ahmadian A, Senu N, De D, Salahshour S (2019d) Disjunctive representation of triangular bipolar neutrosophic numbers, de-bipolarization technique and application in multi-criteria decision-making problems. Symmetry 11(7):932. https://doi.org/10.3390/sym11070932CrossRef Chakraborty A, Mondal SP, Alam S, Ahmadian A, Senu N, De D, Salahshour S (2019d) Disjunctive representation of triangular bipolar neutrosophic numbers, de-bipolarization technique and application in multi-criteria decision-making problems. Symmetry 11(7):932. https://​doi.​org/​10.​3390/​sym11070932CrossRef
Zurück zum Zitat Chakraborty A, Mondal SP, Alam S, Mahata (2019e) Different linear and nonlinear form of trapezoidal neutrosophic numbers, de-neutrosophication techniques and its application in time-cost optimization technique, sequencing problem. RAIRO Oper Res. https://doi.org/10.1051/ro/2019090CrossRef Chakraborty A, Mondal SP, Alam S, Mahata (2019e) Different linear and nonlinear form of trapezoidal neutrosophic numbers, de-neutrosophication techniques and its application in time-cost optimization technique, sequencing problem. RAIRO Oper Res. https://​doi.​org/​10.​1051/​ro/​2019090CrossRef
Zurück zum Zitat Chang SS, Zadeh LA (1972) On fuzzy mappings and control. IEEE Trans Syst Man Cyberne 2:30–34MathSciNetMATH Chang SS, Zadeh LA (1972) On fuzzy mappings and control. IEEE Trans Syst Man Cyberne 2:30–34MathSciNetMATH
Zurück zum Zitat Chen SJ, Chen SM (2003) A new method for handling multicriteria fuzzy decision-making problems using FN-IOWA operators. Cybern Syst 34:109–137MATH Chen SJ, Chen SM (2003) A new method for handling multicriteria fuzzy decision-making problems using FN-IOWA operators. Cybern Syst 34:109–137MATH
Zurück zum Zitat Chen SJ, Chen SM (2007) Fuzzy risk analysis based on the ranking of generalized trapezoidal fuzzy numbers. Appl Intell 26:1–11 Chen SJ, Chen SM (2007) Fuzzy risk analysis based on the ranking of generalized trapezoidal fuzzy numbers. Appl Intell 26:1–11
Zurück zum Zitat Chen SM, Chen JH (2009) Fuzzy risk analysis based on the ranking of generalized fuzzy numbers with different heights and different spreads. Expert Syst Appl 36:6833–6842 Chen SM, Chen JH (2009) Fuzzy risk analysis based on the ranking of generalized fuzzy numbers with different heights and different spreads. Expert Syst Appl 36:6833–6842
Zurück zum Zitat Chen SM, Chen SW (2014) Fuzzy forecasting based on two-factors second-order fuzzy-trend logical relationship groups and the probabilities of trends of fuzzy logical relationships. IEEE Trans Cybern 45(3):391–403 Chen SM, Chen SW (2014) Fuzzy forecasting based on two-factors second-order fuzzy-trend logical relationship groups and the probabilities of trends of fuzzy logical relationships. IEEE Trans Cybern 45(3):391–403
Zurück zum Zitat Chen SM, Hong JA (2014) Fuzzy multiple attributes group decision-making based on ranking interval type-2 fuzzy sets and the TOPSIS method. IEEE Trans Syst Man Cybern 44(12):1665–1673 Chen SM, Hong JA (2014) Fuzzy multiple attributes group decision-making based on ranking interval type-2 fuzzy sets and the TOPSIS method. IEEE Trans Syst Man Cybern 44(12):1665–1673
Zurück zum Zitat Chen SM, Hsiao WH (2000) Bidirectional approximate reasoning for rule-based systems using interval-valued fuzzy sets. Fuzzy Sets Syst 113(2):185–203MathSciNetMATH Chen SM, Hsiao WH (2000) Bidirectional approximate reasoning for rule-based systems using interval-valued fuzzy sets. Fuzzy Sets Syst 113(2):185–203MathSciNetMATH
Zurück zum Zitat Chen LH, Lu HW (2001) An approximate approach for ranking fuzzy numbers based on left and right dominance. Comput Math Appl 41:1589–1602MathSciNetMATH Chen LH, Lu HW (2001) An approximate approach for ranking fuzzy numbers based on left and right dominance. Comput Math Appl 41:1589–1602MathSciNetMATH
Zurück zum Zitat Chen SM, Hsiao WH, Jong WT (1997) Bidirectional approximate reasoning based on interval-valued fuzzy sets. Fuzzy Sets Syst 91(3):339–353MathSciNetMATH Chen SM, Hsiao WH, Jong WT (1997) Bidirectional approximate reasoning based on interval-valued fuzzy sets. Fuzzy Sets Syst 91(3):339–353MathSciNetMATH
Zurück zum Zitat Chen SM, Chang YC, Pan JS (2012a) Fuzzy rules interpolation for sparse fuzzy rule-based systems based on interval type-2 Gaussian fuzzy sets and genetic algorithms. IEEE Trans Fuzzy Syst 21(3):412–425 Chen SM, Chang YC, Pan JS (2012a) Fuzzy rules interpolation for sparse fuzzy rule-based systems based on interval type-2 Gaussian fuzzy sets and genetic algorithms. IEEE Trans Fuzzy Syst 21(3):412–425
Zurück zum Zitat Chen SM, Chu HP, Sheu TW (2012b) TAIEX forecasting using fuzzy time series and automatically generated weights of multiple factors. IEEE Trans Syst Man Cybern Part A 42(6):1485–1495 Chen SM, Chu HP, Sheu TW (2012b) TAIEX forecasting using fuzzy time series and automatically generated weights of multiple factors. IEEE Trans Syst Man Cybern Part A 42(6):1485–1495
Zurück zum Zitat Chen SM, Manalu GMT, Pan JS, Liu HC (2013) Fuzzy forecasting based on two-factors second-order fuzzy-trend logical relationship groups and particle swarm optimization techniques. IEEE Trans Cybern 43(3):1102–1117 Chen SM, Manalu GMT, Pan JS, Liu HC (2013) Fuzzy forecasting based on two-factors second-order fuzzy-trend logical relationship groups and particle swarm optimization techniques. IEEE Trans Cybern 43(3):1102–1117
Zurück zum Zitat Cheng CH (1998) A new approach for ranking fuzzy numbers by distance method. Fuzzy Sets Syst 95:307–317MathSciNetMATH Cheng CH (1998) A new approach for ranking fuzzy numbers by distance method. Fuzzy Sets Syst 95:307–317MathSciNetMATH
Zurück zum Zitat Christi MSA, Kasthuri B (2016) Transportation Problem with Pentagonal Intuitionistic Fuzzy Numbers Solved Using Ranking Technique and Russell’s Method. Int J Eng Res Appl 6:82–86 Christi MSA, Kasthuri B (2016) Transportation Problem with Pentagonal Intuitionistic Fuzzy Numbers Solved Using Ranking Technique and Russell’s Method. Int J Eng Res Appl 6:82–86
Zurück zum Zitat Christi MSA, Priyadharshini N (2017) Stability of the queueing model using DSW model with hexagonal fuzzy number. IMRF J 2017:126–129 Christi MSA, Priyadharshini N (2017) Stability of the queueing model using DSW model with hexagonal fuzzy number. IMRF J 2017:126–129
Zurück zum Zitat Chu T, Tsao C (2002) Ranking fuzzy numbers with an area between the centroid point and original point. Comput Math Appl 43:111–117MathSciNetMATH Chu T, Tsao C (2002) Ranking fuzzy numbers with an area between the centroid point and original point. Comput Math Appl 43:111–117MathSciNetMATH
Zurück zum Zitat Deng Y, Liu Q (2005) A TOPSIS-based centroid index ranking method of fuzzy numbers and its application in decision-making. Cybern Syst 36:581–595MATH Deng Y, Liu Q (2005) A TOPSIS-based centroid index ranking method of fuzzy numbers and its application in decision-making. Cybern Syst 36:581–595MATH
Zurück zum Zitat Deng Y, Zhu ZF, Liu Q (2006) Ranking fuzzy numbers with an area method using of gyration. Comput Math Appl 51:1127–1136MathSciNetMATH Deng Y, Zhu ZF, Liu Q (2006) Ranking fuzzy numbers with an area method using of gyration. Comput Math Appl 51:1127–1136MathSciNetMATH
Zurück zum Zitat Dhurai K, Karpagam A (2016) Fuzzy optimal solution for fully fuzzy linear programming problems using hexagonal fuzzy numbers. Int J Fuzzy Math Arch 10:2320–3250 Dhurai K, Karpagam A (2016) Fuzzy optimal solution for fully fuzzy linear programming problems using hexagonal fuzzy numbers. Int J Fuzzy Math Arch 10:2320–3250
Zurück zum Zitat Dinagar DS, Narayanan UH (2016) On determinant of hexagonal fuzzy number matrices. Int J Math Appl 4:357–363 Dinagar DS, Narayanan UH (2016) On determinant of hexagonal fuzzy number matrices. Int J Math Appl 4:357–363
Zurück zum Zitat Filev DP, Yager RR (1991) A generalized defuzzification method via BADD distributions. Int J Intell Syst 6:687–697MATH Filev DP, Yager RR (1991) A generalized defuzzification method via BADD distributions. Int J Intell Syst 6:687–697MATH
Zurück zum Zitat Garg H, Kumar K (2019) Improved possibility degree method for ranking intuitionistic fuzzy numbers and their application in multiattribute decision-making. Granul Comput 4(2):237–247 Garg H, Kumar K (2019) Improved possibility degree method for ranking intuitionistic fuzzy numbers and their application in multiattribute decision-making. Granul Comput 4(2):237–247
Zurück zum Zitat Ghadle KP, Pathade PA (2017) Solving transportation problem with generalized hexagonal and generalized octagonal fuzzy numbers by ranking method. Glob J Pure Appl Math 13:6367–6376 Ghadle KP, Pathade PA (2017) Solving transportation problem with generalized hexagonal and generalized octagonal fuzzy numbers by ranking method. Glob J Pure Appl Math 13:6367–6376
Zurück zum Zitat Hajjari T (2011a) Ranking of fuzzy numbers based on ambiguity degree. Aust J Basic Appl Sci 5(1):62–69 Hajjari T (2011a) Ranking of fuzzy numbers based on ambiguity degree. Aust J Basic Appl Sci 5(1):62–69
Zurück zum Zitat Hajjari T (2011b) On deviation degree methods for ranking fuzzy numbers. Aust J Basic Appl Sci 5(5):750–758 Hajjari T (2011b) On deviation degree methods for ranking fuzzy numbers. Aust J Basic Appl Sci 5(5):750–758
Zurück zum Zitat Helen R, Uma G (2015) A new operation and ranking on pentagon fuzzy numbers. Int J Math Sci Appl 5:341–346 Helen R, Uma G (2015) A new operation and ranking on pentagon fuzzy numbers. Int J Math Sci Appl 5:341–346
Zurück zum Zitat Jiang T, Li Y (1996) Generalized defuzzification strategies and their parameter learning procedure. IEEE Trans Fuzzy Syst 4:64–71 Jiang T, Li Y (1996) Generalized defuzzification strategies and their parameter learning procedure. IEEE Trans Fuzzy Syst 4:64–71
Zurück zum Zitat Liu XW, Han SL (2005) Ranking fuzzy numbers with preference weighting function expectation. Comput Math Appl 49:1455–1465MathSciNet Liu XW, Han SL (2005) Ranking fuzzy numbers with preference weighting function expectation. Comput Math Appl 49:1455–1465MathSciNet
Zurück zum Zitat Liu W, Li L (2019) Emergency decision-making combining cumulative prospect theory and group decision-making. Granul Comput 4(1):39–52 Liu W, Li L (2019) Emergency decision-making combining cumulative prospect theory and group decision-making. Granul Comput 4(1):39–52
Zurück zum Zitat Liu F, Yuan XH (2007) Fuzzy number intuitionistic fuzzy set. Fuzzy Syst Math 21(1):88–91MATH Liu F, Yuan XH (2007) Fuzzy number intuitionistic fuzzy set. Fuzzy Syst Math 21(1):88–91MATH
Zurück zum Zitat Liu P, Chen SM, Liu J (2017) Multiple attribute group decision making based on intuitionistic fuzzy interaction partitioned Bonferroni mean operators. Inf Sci 411:98–121MathSciNetMATH Liu P, Chen SM, Liu J (2017) Multiple attribute group decision making based on intuitionistic fuzzy interaction partitioned Bonferroni mean operators. Inf Sci 411:98–121MathSciNetMATH
Zurück zum Zitat Liu P, Liu J, Chen SM (2018) Some intuitionistic fuzzy Dombi Bonferroni mean operators and their application to multi-attribute group decision making. J Oper Res Soc 69(1):1–24MathSciNet Liu P, Liu J, Chen SM (2018) Some intuitionistic fuzzy Dombi Bonferroni mean operators and their application to multi-attribute group decision making. J Oper Res Soc 69(1):1–24MathSciNet
Zurück zum Zitat Mary A, Sivasankari R (2016) Direct method of fuzzy transportation problem using hexagonal fuzzy number with alpha cut. Int J Math Appl 4:373–379 Mary A, Sivasankari R (2016) Direct method of fuzzy transportation problem using hexagonal fuzzy number with alpha cut. Int J Math Appl 4:373–379
Zurück zum Zitat Mondal SP, Mandal M (2018) Nonlinear interval-valued fuzzy numbers and their application in difference equations. Granul Comput 3(2):177–189 Mondal SP, Mandal M (2018) Nonlinear interval-valued fuzzy numbers and their application in difference equations. Granul Comput 3(2):177–189
Zurück zum Zitat Panda A, Pal M (2015) A study on pentagonal fuzzy number and its corresponding matrices. Pac Sci Rev B 1:131–139 Panda A, Pal M (2015) A study on pentagonal fuzzy number and its corresponding matrices. Pac Sci Rev B 1:131–139
Zurück zum Zitat Raj AV, Ezhilarasi V (2016) Ranking of generalized hexagonal fuzzy numbers based on rank, mode, divergence and spread. Int J Math Appl 4:349–355 Raj AV, Ezhilarasi V (2016) Ranking of generalized hexagonal fuzzy numbers based on rank, mode, divergence and spread. Int J Math Appl 4:349–355
Zurück zum Zitat Rajarajeswari P, Sudha AS (2014) Ordering generalized hexagonal fuzzy numbers using rank, mode, divergence and spread. IOSR J Math (IOSR-JM) 10:15–22 Rajarajeswari P, Sudha AS (2014) Ordering generalized hexagonal fuzzy numbers using rank, mode, divergence and spread. IOSR J Math (IOSR-JM) 10:15–22
Zurück zum Zitat Rajarajeswari P, Sudha AS, Karthika R (2013) A new operation on hexagonal fuzzy number. Int J Fuzzy Logic Syst 3:15–26 Rajarajeswari P, Sudha AS, Karthika R (2013) A new operation on hexagonal fuzzy number. Int J Fuzzy Logic Syst 3:15–26
Zurück zum Zitat Smarandache FA (1998) Unifying field in logics neutrosophy: neutrosophic probability, set and logic. American Research Press, RehobothMATH Smarandache FA (1998) Unifying field in logics neutrosophy: neutrosophic probability, set and logic. American Research Press, RehobothMATH
Zurück zum Zitat Song Q, Leland RP (1996) Adaptive learning defuzzification techniques and applications. Comput Math Appl 81:321–329 Song Q, Leland RP (1996) Adaptive learning defuzzification techniques and applications. Comput Math Appl 81:321–329
Zurück zum Zitat Sudha AS, Revathy M (2014) Arithmetic operations on intuitionistic hexagonal fuzzy numbers using α cut. Int J Recent Innov Trends Comput Commun 5:696–704 Sudha AS, Revathy M (2014) Arithmetic operations on intuitionistic hexagonal fuzzy numbers using α cut. Int J Recent Innov Trends Comput Commun 5:696–704
Zurück zum Zitat Sudha AS, Revathy M (2016) A new ranking of hexagonal fuzzy numbers. Int J Fuzzy Logic Syst 6:1–8 Sudha AS, Revathy M (2016) A new ranking of hexagonal fuzzy numbers. Int J Fuzzy Logic Syst 6:1–8
Zurück zum Zitat Thamaraiselvi A, Santhi R (2015) Solving fuzzy transportation problem with generalized hexagonal fuzzy numbers. IOSR J Math 11:8–13 Thamaraiselvi A, Santhi R (2015) Solving fuzzy transportation problem with generalized hexagonal fuzzy numbers. IOSR J Math 11:8–13
Zurück zum Zitat Turksen IB (1986) Interval valued fuzzy sets based on normal forms. Fuzzy Sets Syst 20:191–210MathSciNetMATH Turksen IB (1986) Interval valued fuzzy sets based on normal forms. Fuzzy Sets Syst 20:191–210MathSciNetMATH
Zurück zum Zitat Wang YJ, Lee HS (2008) The revised method of ranking fuzzy numbers with an area between the centroid and original points. Comput Math Appl 55:2033–2042MathSciNetMATH Wang YJ, Lee HS (2008) The revised method of ranking fuzzy numbers with an area between the centroid and original points. Comput Math Appl 55:2033–2042MathSciNetMATH
Zurück zum Zitat Wang ZX, Liu YJ, Fan ZP, Feng B (2009) Ranking L–R fuzzy numbers based on deviation degree. Inform Sci 176:2070–2077MathSciNetMATH Wang ZX, Liu YJ, Fan ZP, Feng B (2009) Ranking L–R fuzzy numbers based on deviation degree. Inform Sci 176:2070–2077MathSciNetMATH
Zurück zum Zitat Yager RR (1996) Knowledge-based defuzzification. Fuzzy Sets Syst 80:177–185MathSciNet Yager RR (1996) Knowledge-based defuzzification. Fuzzy Sets Syst 80:177–185MathSciNet
Zurück zum Zitat Ye J (2014) Prioritized aggregation operators of trapezoidal intuitionistic fuzzy sets and their application to multi criteria decision making. Neural Comput Appl 25(6):1447–1454 Ye J (2014) Prioritized aggregation operators of trapezoidal intuitionistic fuzzy sets and their application to multi criteria decision making. Neural Comput Appl 25(6):1447–1454
Zurück zum Zitat Zadeh LA (1965) Fuzzy sets. Inf Control 8(5):338–353MATH Zadeh LA (1965) Fuzzy sets. Inf Control 8(5):338–353MATH
Zurück zum Zitat Zeng S, Chen SM, Kuo LW (2019) Multiattribute decision making based on novel score function of intuitionistic fuzzy values and modified VIKOR method. Inf Sci 488:76–92 Zeng S, Chen SM, Kuo LW (2019) Multiattribute decision making based on novel score function of intuitionistic fuzzy values and modified VIKOR method. Inf Sci 488:76–92
Metadaten
Titel
Hexagonal fuzzy number and its distinctive representation, ranking, defuzzification technique and application in production inventory management problem
verfasst von
Avishek Chakraborty
Suman Maity
Shalini Jain
Sankar Prasad Mondal
Shariful Alam
Publikationsdatum
21.02.2020
Verlag
Springer International Publishing
Erschienen in
Granular Computing / Ausgabe 3/2021
Print ISSN: 2364-4966
Elektronische ISSN: 2364-4974
DOI
https://doi.org/10.1007/s41066-020-00212-8

Weitere Artikel der Ausgabe 3/2021

Granular Computing 3/2021 Zur Ausgabe