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Combining conflicting evidence using the DEMATEL method

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Abstract

Dempster–Shafer evidence theory is widely used in the information fusion field for its effectivity in representing and handling uncertain information. However, applications of Dempster rule in combining multiple conflicting evidence often cause counterintuitive results. One of the existing researches on conflict is based on the similarity of evidence. However, due to the fact that computational complexity of the existing methods is large, it is difficult to meet the real-time requirements of systems. Therefore, new effective methods with acceptable expense should be explored. In this article, following the idea of modifying the source model of evidence, a new method based on DEMATEL is proposed to take the weight of each evidence into consideration. First, the total-relation matrix is determined by the similarity among evidence. Second, prominence and importance are calculated. Finally, the weighted average combination result can be obtained based on Dempster’s rule of combination. Numerical examples are used to demonstrate that the proposed model is efficient to both deals with conflicting evidence and reduce computational complexity.

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References

  • Altınçay H (2006) On the independence requirement in dempster-shafer theory for combining classifiers providing statistical evidence. Appl Intell 25(1):73–90

    MATH  Google Scholar 

  • Basseville M (1989) Distance measures for signal processing and pattern recognition. Eur J Signal Process 18(4):349–369

    MathSciNet  Google Scholar 

  • Beynon M, Curry B, Morgan P (2000) The dempstershafer theory of evidence: an alternative approach to multicriteria decision modeling. Expert Syst Appl 38(4):37–50

    Google Scholar 

  • Bian T, Deng Y (2018) Identifying influential nodes in complex networks: A node information dimension approach. Chaos Interdiscip J Nonlinear Sci. https://doi.org/10.1063/1.5030894

  • Bian T, Zheng H, Yin L, Deng Y (2018) Failure mode and effects analysis based on Dnumbers and topsis. Qual Reliab Eng Int. https://doi.org/10.1002/qre.2268

    Article  Google Scholar 

  • Cha SH (2007) Comprehensive survey on distance/similaritymeasures between probability density functions. Int J Math Models Methods Appl Sci 1(4):300–307

    Google Scholar 

  • Chen L, Deng X (2018) A modified method for evaluating sustainable transport solutions based on ahp and dempstershafer evidence theory. Appl Sci. https://doi.org/10.3390/app8040563

    Article  Google Scholar 

  • Dempster AP (1967) Upper and lower probabilities induced by a multivariate mapping. Ann Math Stat 38:325–339

    MATH  Google Scholar 

  • Deng W, Lu X, Deng Y (2018) Evidential model validation under epistemic uncertainty. Math Prob Eng. https://doi.org/10.1155/2018/6789635

    Article  MathSciNet  Google Scholar 

  • Deng X, Deng Y (2018) D-AHP method with different credibility of information. Soft Comput. https://doi.org/10.1007/s00,500-017-2993-9

    Article  Google Scholar 

  • Deng X, Jiang W (2018) Dependence assessment in human reliability analysis using an evidential network approach extended by belief rules and uncertainty measures. Ann Nucl Energy 117:183–193

    Google Scholar 

  • Deng X, Jiang W (2018) An evidential axiomatic design approach for decision making using the evaluation of belief structure satisfaction to uncertain target values. Int J Intell Syst 33(1):15–32

    Google Scholar 

  • Deng Y, Shi WK, Zhu ZZ, Liu Q (2004) Combining belief functions based on distance of evidence. Decis Support Syst 38(3):489–493

    Google Scholar 

  • Dong Y, Wang J, Chen F, Hu Y, Deng Y (2017) Location of facility based on simulated annealing and “ZKW” algorithms. Math Prob Eng. https://doi.org/10.1155/2017/4628501

  • Dubois D, Prade H (1988) Representation and combination of uncertainty with belief functions and possibility measures. Comput Intell 4(3):244–264

    Google Scholar 

  • Florea M, Jousselme A, Bosse E (2009) Robust combination rules for evidence theory. Inf Fusion 10(2):183–197

    Google Scholar 

  • Fontela E, Gabus A (1976) The DEMATEL Observer. Battelle Geneva Research Center, Geneva

    Google Scholar 

  • Frikha A, Moalla H (2014) Analytic hierarchy process for multi-sensor data fusion based on belief function theory. Eur J Oper Res 241(1):133–147

    MathSciNet  MATH  Google Scholar 

  • Gabus A, Fontela E (1972) World Problems, an Invitation to further thought within the framework of DEMATEL. Battelle Geneva Research Center, Geneva

    Google Scholar 

  • Haenni A (2002) Are alternatives to dempster’s rule of combination real alternatives: Comments on about the belief function combination and the conflict management problem-lefevre, et al. Inf Fusion 3(3):237–239

  • Haenni R (2005) Shedding new light on zadeh’s criticism of dempster’s rule of combination. In: 2005 7th international conference on information fusion, vol 2. IEEE, pp 6

  • Jiang W, Wang S (2017) An uncertainty measure for interval-valued evidences. Int J Comput Commun Control 12(5):631–644

    MathSciNet  Google Scholar 

  • Jiang W, Wang S, Liu X, Zheng H, Wei B (2017) Evidence conflict measure based on OWA operator in open world. PloS ONE 12(5):e0177,828

  • Jiang W, Wei B (2018) Intuitionistic fuzzy evidential power aggregation operator and its application in multiple criteria decision-making. Int J Syst Sci 49(3):582–594

    MathSciNet  MATH  Google Scholar 

  • Jiang W, Wei B, Liu X, Li X, Zheng H (2018) Intuitionistic fuzzy power aggregation operator based on entropy and its application in decision making. Int J Intell Syst 33(1):49–67

    Google Scholar 

  • Jiang W, Wei B, Qin X, Zhan J, Tang Y (2016) Sensor data fusion based on a new conflict measure. Math Prob Eng 2016:11

    MathSciNet  MATH  Google Scholar 

  • Jousselme AL, Grenier D, Bosse E (2001) A new distance between two bodies of evidence. Inf Fusion 2(2):91–101

    Google Scholar 

  • Kang B, Chhipi-Shrestha G, Deng Y, Hewage K, Sadiq R (2018) Stable strategies analysis based on the utility of Z-number in the evolutionary games. Appl Math Comput 324:202–217

    MathSciNet  MATH  Google Scholar 

  • Kang B, Deng Y (2018) Generating Z-number based on OWA weights usingmaximum entropy. Int J Intell Syst. https://doi.org/10.1002/int.21995

    Article  Google Scholar 

  • Lefèvre E, Colot O, Vannoorenberghe P (2002) Belief function combination and conflict management. Inf Fusion 3(2):149–162

    Google Scholar 

  • Lefèvre E, Elouedi Z (2013) How to preserve the conflict as an alarm in the combination of belief functions? Decis Support Syst 56:326–333

    Google Scholar 

  • Li M, Zhang Q, Deng Y (2018) Evidential identification of influential nodes in network of networks. Chaos Solitons Fractals. https://doi.org/10.1016/j.chaos.2018.04.033

    Article  MathSciNet  Google Scholar 

  • Li X, Jusup M, Wang Z, Li H, Shi L, Podobnik B, Stanley HE, Havlin S, Boccaletti S (2017) Punishment diminishes the benefits of network reciprocity in social dilemma experiments. Proc Natl Acad Sci. https://doi.org/10.1073/pnas.1707505,115

    Article  Google Scholar 

  • Li Y, Hu Y, Zhang X, Deng Y, Mahadevan S (2014) An evidential dematel method to identify critical success factors inemergency management. Appl Soft Comput J 22:504–510

    Google Scholar 

  • Lin Y, Wang C, Ma C, Dou Z, Ma X (2016) A new combination method for multisensor conflict information. J Supercomput 72(7):1–17

    Google Scholar 

  • Liou J (2015) Building an effective system for carbon reduction management. J Clean Prod 103:353–361

    Google Scholar 

  • Liu T, Deng Y, Chan F (2017) Evidential supplier selection based on DEMATEL and game theory. Int J Fuzzy Syst. https://doi.org/10.1007/s40,815-017-0400-4

    Article  Google Scholar 

  • Liu W (2006) Analyzing the degree of conflict among belief functions. Artif Intell 170(11):909–924

    MathSciNet  MATH  Google Scholar 

  • Lo CC, Chen WJ (2012) A hybrid information security risk assessment procedure considering interdependences between controls. Expert Syst Appl 39(1):247–257

    Google Scholar 

  • Ma J, Liu W, Miller P, Zhou H (2016) An evidential fusion approach for gender profiling. Inf Sci 333:10–20

    Google Scholar 

  • Mo H, Deng Y (2016) A new aggregating operator in linguistic decision making based on D numbers. Int J Uncertain Fuzziness Know Based Syst 24(6):831–846

    MATH  Google Scholar 

  • Mönks U, Dörksen H, Lohweg V, Hübner M (2016) Information fusion of conflicting input data. Sensors 16(11):1798

    Google Scholar 

  • Murphy C (2000) Combining belief functions when evidence conflicts. Decis Support Syst 29(1):1–9

    Google Scholar 

  • Perez A, Tabia H, Declercq D, Zanotti A (2016) Using the conflict in dempstershafer evidence theory as a rejection criterion in classifier output combination for 3d human action recognition. Image Vis Comput 55:149–157

    Google Scholar 

  • Shafer G (1976) A mathematical theory of evidence, vol 1. Princeton University Press, Princeton

    MATH  Google Scholar 

  • Smets P, Kennes R (1994) The transferable belief model. Artif Intell 66(2):191–234

    MathSciNet  MATH  Google Scholar 

  • Tseng ML (2009) A causal and effect decision making model of service quality expectation using grey-fuzzy dematel approach. Expert Syst Appl 36(4):7738–7748

    Google Scholar 

  • Tzeng GH, Chiang CH, Li CW (2007) Evaluating intertwined effects in e-learning programs: a novel hybrid mcdm model based on factor analysis and dematel. Expert Syst Appl 32(4):1028–1044

    Google Scholar 

  • Wu HH, Chen HK, Shieh JI (2010) Evaluating performance criteria of employment service outreach program personnel by dematel method. Expert Syst Appl 37(7):5219–5223

    Google Scholar 

  • Xiao F (2018) A hybrid fuzzy soft sets decision making method in medical diagnosis. IEEE Access. https://doi.org/10.1109/ACCESS.2018.2820099

    Article  Google Scholar 

  • Xiao F (2018) An improved method for combining conflicting evidences based on the similarity measure and belief function entropy. Int J Fuzzy Syst 20(4):1256–1266

    MathSciNet  Google Scholar 

  • Xiao F (2018) A novel multi-criteria decision making method for assessing health-care waste treatment technologies based on D numbers. Eng Appl Artif Intell 71(2018):216–225

    Google Scholar 

  • Xiao F, Zhan C, Lai H, Tao L, Qu Z (2017) New parallel processing strategies in complex event processing systems with data streams. Int J Distrib Sens Netw 13(8):1–15

    Google Scholar 

  • Xu H, Deng Y (2018) Dependent evidence combination based on shearman coefficient and pearson coefficient. IEEE Access 6(1):11634–11640

    Google Scholar 

  • Yager RR (1987) On the dempster-shafer framework and new combination rules. Inf Sci 41(2):93–137

    MathSciNet  MATH  Google Scholar 

  • Yaowen FU, Wei Y (2014) Combination rule based on proportional redistribution of generalized conflict for evidence theory. Chin J Electron 23(3):533–538

    Google Scholar 

  • Yin L, Deng Y (2018) Toward uncertainty of weighted networks: An entropy-based model. Phys A Stat Mech Appl. https://doi.org/10.1016/j.physa.2018.05.067

    Article  Google Scholar 

  • Yu Y, Xiao G, Zhou J, Wang Y, Wang Z, Kurths J, Schellnhuber HJ (2016) System crash as dynamics of complex networks. Proc Nat Acad Sci 113(42):11726–11731

    MathSciNet  MATH  Google Scholar 

  • Zadeh L (1986) A simple view of the Dempster–Shafer theory of evidence and its implication for the rule of combination. AI Mag 7(2):85

    Google Scholar 

  • Zhang L, Wu X, Zhu H, Abourizk SM (2017) Perceiving safety risk of buildings adjacent to tunneling excavation: an information fusion approach. Autom Constr 73:88–101

    Google Scholar 

  • Zhang Q, Li M, Deng Y (2018) Measure the structure similarity of nodes in complex networks based on relative entropy. Phys A Stat Mech Appl 491:749–763

    MathSciNet  Google Scholar 

  • Zhang R, Ashuri B, Deng Y (2017) A novel method for forecasting time series based on fuzzy logic and visibility graph. Adv Data Anal Classif 11(4):759–783

    MathSciNet  MATH  Google Scholar 

  • Zhang Z, Liu T, Chen D, Zhang W (2014) Novel algorithm for identifying and fusing conflicting data in wireless sensor networks. Sensors 14(6):9562–9581

    Google Scholar 

  • Zheng H, Deng Y (2017) Evaluation method based on fuzzy relations between Dempster-Shafer belief structure. Int J Intell Syst. https://doi.org/10.1002/int.21956

    Article  Google Scholar 

  • Zheng H, Deng Y, Hu Y (2017) Fuzzy evidential influence diagram and its evaluation algorithm. Knowl Based Syst 131:28–45

    Google Scholar 

  • Zheng X, Deng Y (2018) Dependence assessment in human reliability analysis based on evidence credibility decay model and iowa operator. Ann Nuclear Energy 112:673–684

    Google Scholar 

  • Zhou X, Deng X, Deng Y, Mahadevan S (2017) Dependence assessment in human reliability analysis based on D numbers and AHP. Nucl Eng Des 313:243–252

    Google Scholar 

  • Zhou X, Hu Y, Deng Y, Chan FTS, Ishizaka A (2018) A DEMATEL-Based completion method for incomplete pairwise comparison matrix in AHP. Ann Oper Res. https://doi.org/10.1007/s10479-018-2769-3

    Article  MathSciNet  MATH  Google Scholar 

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Acknowledgements

The work is partially supported by National Natural Science Foundation of China (Grant Nos. 61573290, 61503237). The authors greatly appreciate the reviews’ suggestions and the editor’s encouragement.

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Authors and Affiliations

  1. School of Physics, University of Electronic Science and Technology of China, Chengdu, 610054, China

    Weiquan Zhang

  2. Institute of Fundamental and Frontier Science, University of Electronic Science and Technology of China, Chengdu, 610054, China

    Yong Deng

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  1. Weiquan Zhang
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  2. Yong Deng
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Correspondence to Yong Deng.

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Zhang, W., Deng, Y. Combining conflicting evidence using the DEMATEL method. Soft Comput 23, 8207–8216 (2019). https://doi.org/10.1007/s00500-018-3455-8

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