Skip to main content
Disciplines
Automotive Business IT + Informatics Construction + Real Estate Electrical Engineering + Electronics Energy + Sustainability Insurance + Risk Finance + Banking Management + Leadership Marketing + Sales Mechanical Engineering + Materials
Events
DE
EN
Books
Journals
Topic Page
Marketing
Start single access now
Access for companies
EXTENDED SEARCH
Log in
Top
International Journal of Machine Learning and Cybernetics
Published in: International Journal of Machine Learning and Cybernetics 6/2018

01-03-2017 | Original Article

A linguistic intuitionistic multi-criteria decision-making method based on the Frank Heronian mean operator and its application in evaluating coal mine safety

Authors: Hong-gang Peng, Jian-qiang Wang, Peng-fei Cheng

Published in: International Journal of Machine Learning and Cybernetics | Issue 6/2018

Log in

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

Coal mine safety has been a pressing issue for many years, and it is a constant and non-negligible problem that must be addressed during any coal mining process. This paper focuses on developing an innovative multi-criteria decision-making (MCDM) method to address coal mine safety evaluation problems. Because lots of uncertain and fuzzy information exists in the process of evaluating coal mine safety, linguistic intuitionistic fuzzy numbers (LIFNs) are introduced to depict the evaluation information necessary to the process. Furthermore, the handling of qualitative information requires the effective support of quantitative tools, and the linguistic scale function (LSF) is therefore employed to deal with linguistic intuitionistic information. First, the distance, a valid ranking method, and Frank operations are proposed for LIFNs. Subsequently, the linguistic intuitionistic fuzzy Frank improved weighted Heronian mean (LIFFIWHM) operator is developed. Then, a linguistic intuitionistic MCDM method for coal mine safety evaluation is constructed based on the developed operator. Finally, an illustrative example is provided to demonstrate the proposed method, and its feasibility and validity are further verified by a sensitivity analysis and comparison with other existing methods.
previous article Data sanitization against adversarial label contamination based on data complexity

Dont have a licence yet? Then find out more about our products and how to get one now:

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!

inform now

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!

inform now

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!

inform now
Show more products
Appendix
Available only for authorised users
Literature
1.
2.
Wei CF, Yuan RF (2010) A decision-making method based on linguistic aggregation operators for coal mine safety evaluation. Intelligent Systems and Knowledge Engineering (ISKE), 2010 International Conference on 17–20
3.
4.
Peng HG, Zhang HY, Wang JQ (2016) Probability multi-valued neutrosophic sets and its application in multi-criteria group decision-making problems. Neural Comput Appl. doi:10.​1007/​s00521-016-2702-0
5.
6.
Urena R, Chiclana F, Fujita H, Herrera-Viedma E (2015) Confidence-consistency driven group decision making approach with incomplete reciprocal intuitionistic preference relations. Knowl Based Syst 89:86–96CrossRef
7.
8.
Torra V, Narukawa Y (2009) On hesitant fuzzy sets and decision. In: The 18th IEEE International Conference on Fuzzy Systems, p 1378–1382
9.
Rodríguez RM, Bedregal B, Bustince H, Dong YC, Farhadinia B, Kahraman C, Martinez L, Torra V, Xu YJ, Xu ZS, Herrera F (2016) A position and perspective analysis of hesitant fuzzy sets on information fusion in decision making. Towards high quality progress. Inf Fusion 29:89–97CrossRef
10.
11.
Martínez L, Ruan D, Herrera F, Herrera-Viedma E, Wang PP (2009) Linguistic decision making:tools and applications. Inf Sci 179(14):2297–2298CrossRef
12.
Liu PD, Wang Y (2016) The aggregation operators based on the 2-dimension uncertain linguistic information and their application to decision making. Int J Mach Learn Cybern 7(6):1057–1074CrossRef
13.
Peng HG, Wang JQ (2016) Hesitant uncertain linguistic Z-numbers and their application in multi-criteria group decision-making problems. Int J Fuzzy Syst. doi:10.​1007/​s40815-016-0257-y
14.
Morente-Molinera JA, Pérez IJ, Ureña MR, Herrera-Viedma E (2015) Building and managing fuzzy ontologies with heterogeneous linguistic information. Knowl Based Syst 88(C):154–164CrossRef
15.
Xu ZS (2004) A method based on linguistic aggregation operators for group decision making with linguistic preference relations. Inf Sci 166(1–4):19–30MathSciNetCrossRefMATH
16.
Xu ZS (2004) Uncertain linguistic aggregation operators based approach to multiple attribute group decision making under uncertain linguistic environment. Inf Sci 168(1):171–184CrossRefMATH
17.
Xu ZS (2006) An approach based on the uncertain LOWG and induced uncertain LOWG operators to group decision making with uncertain multiplicative linguistic preference relations. Decis Support Syst 41(2):488–499CrossRef
18.
Wei GW, Zhao XF, Lin R, Wang HJ (2013) Uncertain linguistic Bonferroni mean operators and their application to multiple attribute decision making. Appl Math Modell 37(7):5277–5285MathSciNetCrossRef
19.
Tian ZP, Wang J, Wang JQ, Zhang HY (2016) A likelihood-based qualitative flexible approach with hesitant fuzzy linguistic information. Cogn Comput 8(4):670–683CrossRef
20.
Zhang Z, Wu C (2014) Hesitant fuzzy linguistic aggregation operators and their applications to multiple attribute group decision making. J Intell Fuzzy Syst 26(5):2185–2202MathSciNetMATH
21.
Zhou H, Wang JQ, Zhang HY (2016) Multi-criteria decision-making approaches based on distance measures for linguistic hesitant fuzzy sets. J Oper Res Soc. doi:10.​1057/​jors.​2016.​41
22.
Wang J, Wang JQ, Zhang HY (2016) A likelihood-based TODIM approach based on multi-hesitant fuzzy linguistic information for evaluation in logistics outsourcing. Comput Ind Eng 99:287–299CrossRef
23.
Chen ZC, Liu PH, Pei Z (2015) An approach to multiple attribute group decision making based on linguistic intuitionistic fuzzy numbers. Int J Comput Intell Syst 8(4):747–760CrossRef
24.
25.
Massanet S, Riera JV, Torrens J, Herrera-Viedma E (2014) A new linguistic computational model based on discrete fuzzy numbers for computing with words. Inf Sci 258(3):277–290MathSciNetCrossRefMATH
26.
Morente-Molinera JA, Pérez IJ, Ureña MR (2015) On multi-granular fuzzy linguistic modeling in group decision making problems: a systematic review and future trends. Knowl Based Syst 74:49–60CrossRef
27.
Zhou SM, Chiclana F, John RI (2008) Type-1 OWA operators for aggregating uncertain information with uncertain weights induced by type-2 linguistic quantifiers. Fuzzy Sets Syst 159(24):3281–3296MathSciNetCrossRefMATH
28.
29.
Zhang HY, Ji P, Wang JQ, Chen XH (2016) A neutrosophic normal cloud and its application in decision-making. Cogn Comput 8(4):649–669CrossRef
30.
Wang JQ, Peng JJ, Zhang HY, Liu T, Chen XH (2015) An uncertain linguistic multi-criteria group decision-making method based on a cloud model. Group Decis Negot 24(1):171–192CrossRef
31.
Herrera F, Martínez L (2000) A 2-tuple fuzzy linguistic representation model for computing with words. IEEE Trans Fuzzy Syst 8(6):746–752CrossRef
32.
Wang JH, Hao JY (2006) A new version of 2-tuple fuzzy linguistic representation model for computing with words. IEEE Trans Fuzzy Syst 14(3):435–445CrossRef
33.
Dong YC, Xu Y, Yu S (2009) Computing the numerical scale of the linguistic term set for the 2-tuple fuzzy linguistic representation model. IEEE Trans Fuzzy Syst 17(6):1366–1378CrossRef
34.
Dong YC, Zhang GQ, Hong WC, Yu S (2013) Linguistic computational model based on 2-tuples and intervals. IEEE Trans Fuzzy Syst 21(6):1006–1018CrossRef
35.
Wang JQ, Wu JT, Wang J, Zhang HY, Chen XH (2014) Interval-valued hesitant fuzzy linguistic sets and their applications in multi-criteria decision-making problems. Inf Sci 288(1):55–72MathSciNetCrossRefMATH
36.
Wang MX, Wang JQ (2016) An evolving Takagi–Sugeno model based on aggregated trapezium clouds for anomaly detection in large datasets. J Intell Fuzzy Syst. doi:10.​3233/​JIFS-16254
37.
Tian ZP, Wang J, Wang JQ, Zhang HY (2016) Multi-criteria decision-making based on generalized prioritized aggregation operators under simplified neutrosophic uncertain linguistic environment. Int J Mach Learn Cybern. doi:10.​1007/​s13042-016-0552-9
38.
Beliakov G, Pradera A, Calvo T (2007) Aggregation functions:a guide for practitioners. Springer, HeidelbergMATH
39.
Liu PD, Shi LL (2015) Some neutrosophic uncertain linguistic number Heronian mean operators and their application to multi-attribute group decision making. Neural Comput Appl. doi:10.​1007/​s00521-015-2122-6
40.
Yu DJ (2013) Intuitionistic fuzzy geometric Heronian mean aggregation operators. Appl Soft Comput 13(2):1235–1246MathSciNetCrossRef
41.
Frank MJ (1979) On the simultaneous associativity of F (x,y) and x + y − F (x,y). Aequ Math 19(1):194–226CrossRefMATH
42.
Ji P, Wang JQ, Zhang HY (2016) Frank prioritized Bonferroni mean operator with single-valued neutrosophic sets and its application in selecting third party logistics. Neural Comput Appl. doi:10.​1007/​s00521-016-2660-6
43.
Zhang X, Liu PD, Wang YM (2015) Multiple attribute group decision making methods based on intuitionistic fuzzy frank power aggregation operators. J Intell Fuzzy Syst 29(5):2235–2246MathSciNetCrossRefMATH
44.
Zhang ZM (2016) Interval-valued intuitionistic fuzzy Frank aggregation operators and their applications to multiple attribute group decision making. Neural Comput Appl. doi:10.​1007/​s00521-015-2143-1
45.
Qin JD, Liu XW, Pedrycz W (2015) Frank aggregation operators and their application to hesitant fuzzy multiple attribute decision making. Appl Soft Comput 41:428–452CrossRef
46.
Dong YC, Herrera-Viedma E (2015) Consistency-driven automatic methodology to set interval numerical scales of 2-tuple linguistic term sets and its use in the linguistic GDM with preference relations. IEEE Trans Cybern 45(4):780–792CrossRef
47.
Dong YC, Li CC, Xu YF, Gu X (2015) Consensus-based group decision making under multi-granular unbalanced 2-tuple linguistic preference relations. Group Decis Negot 24(2):217–242CrossRef
48.
Dong YC, Chen X, Liang HM, Li CC (2016) Dynamics of linguistic opinions formation in bounded confidence model. Inf Fusion 32:52–61CrossRef
49.
Bao GY, Lian XL, He M, Wang LL (2010) Improved two-tuple linguistic representation model based on new linguistic evaluation scale. Control Decis 25(5):780–784MathSciNet
50.
Kahneman D, Tversky A (1979) Prospect theory:an analysis of decision under risk. Econometrica 47(2):263–291CrossRefMATH
51.
Dong Y, Li CC, Herrera F (2016) Connecting the linguistic hierarchy and the numerical scale for the 2-tuple linguistic model and its use to deal with hesitant unbalanced linguistic information. Inf Sci 367–368:259–278CrossRef
52.
Dong YC, Xu YF, Li HY, Feng B (2010) The OWA-based consensus operator under linguistic representation models using position indexes. Eur J Oper Res 203(2):455–463CrossRefMATH
53.
Li CC, Dong YC, Herrera F, Herrera-Viedma E, Martínez L (2017) Personalized individual semantics in computing with words for supporting linguistic group decision making. An application on consensus reaching. Inf Fusion 33(C):29–40
54.
Szmidt E, Kacprzyk J (2009) Ranking of intuitionistic fuzzy alternatives in a multi-criteria decision making problem. NAFIPS 2009–2009 Annual Meeting of the North American Fuzzy Information Processing Society
55.
Dong YC, Zhang HJ, Herrera-Viedma E (2016) Integrating experts’ weights generated dynamically into the consensus reaching process and its applications in managing non-cooperative behaviors. Decis Support Syst 84:1–15CrossRef
Metadata
Title
A linguistic intuitionistic multi-criteria decision-making method based on the Frank Heronian mean operator and its application in evaluating coal mine safety
Authors
Hong-gang Peng
Jian-qiang Wang
Peng-fei Cheng
Publication date
01-03-2017
Publisher
Springer Berlin Heidelberg
Published in
International Journal of Machine Learning and Cybernetics / Issue 6/2018
Print ISSN: 1868-8071
Electronic ISSN: 1868-808X
DOI
https://doi.org/10.1007/s13042-016-0630-z

Other articles of this Issue 6/2018

International Journal of Machine Learning and Cybernetics 6/2018 Go to the issue

Original Article

An ordered clustering algorithm based on K-means and the PROMETHEE method

Original Article

A transplantation of subject-independent model in cross-platform BCI

Original Article

filter design for delayed static neural networks with Markovian switching and randomly occurred nonlinearity

Original Article

Estimated plant’s sensitivity based on data-driving observer for a class of nonlinear discrete-time control systems

Original Article

Arrow detection in biomedical images using sequential classifier

Original Article

Local mean representation based classifier and its applications for data classification