A variable weight approach for evidential reasoning

A variable weight approach was proposed to handle the probability deficiency problem in the evidential reasoning (ER) approach. The probability deficiency problem indicated that the inadequate information in the assessment result should be less than that in the input. However, it was proved that under certain circumstances, the ER approach could not solve the probability deficiency problem. The variable weight approach was based on two assumptions: 1) the greater weight should be given to the rule with more adequate information; 2) the greater weight should be given to the rules with less disparate information. Assessment results of two notional case studies show that 1) the probability deficiency problem is solved using the proposed variable weight approach, and 2) the information with less inadequacy and more disparity is provided for the decision makers to help reach a consensus.

[1]  N. Kerr,et al.  Group performance and decision making. , 2004, Annual review of psychology.

[2]  Volker C. Franke Decision-Making under Uncertainty: Using Case Studies for Teaching Strategy in Complex Environments , 2011 .

[3]  Anne-Laure Jousselme,et al.  Distances in evidence theory: Comprehensive survey and generalizations , 2012, Int. J. Approx. Reason..

[4]  Jian-Bo Yang,et al.  Integrated efficiency and trade-off analyses using a DEA-oriented interactive minimax reference point approach , 2012, Comput. Oper. Res..

[5]  G. Stasser,et al.  Pooling of Unshared Information in Group Decision Making: Biased Information Sampling During Discussion , 1985 .

[6]  Éloi Bossé,et al.  A new distance between two bodies of evidence , 2001, Inf. Fusion.

[7]  Thierry Denux Reasoning with imprecise belief structures , 1999 .

[8]  Jian-Bo Yang,et al.  Environmental impact assessment using the evidential reasoning approach , 2006, Eur. J. Oper. Res..

[9]  G. Apostolakis The concept of probability in safety assessments of technological systems. , 1990, Science.

[10]  Shanlin Yang,et al.  The combination of dependence-based interval-valued evidential reasoning approach with balanced scorecard for performance assessment , 2012, Expert Syst. Appl..

[11]  T. Denœux Conjunctive and disjunctive combination of belief functions induced by nondistinct bodies of evidence , 2008 .

[12]  Jon C. Helton,et al.  Challenge Problems : Uncertainty in System Response Given Uncertain Parameters ( DRAFT : November 29 , 2001 ) , 2001 .

[13]  Jon C. Helton,et al.  Alternative representations of epistemic uncertainty , 2004, Reliab. Eng. Syst. Saf..

[14]  Arthur P. Dempster,et al.  Upper and Lower Probabilities Induced by a Multivalued Mapping , 1967, Classic Works of the Dempster-Shafer Theory of Belief Functions.

[15]  Ying-Wu Chen,et al.  TOPSIS with belief structure for group belief multiple criteria decision making , 2010, Int. J. Autom. Comput..

[16]  Jian-Bo Yang,et al.  Belief rule-base inference methodology using the evidential reasoning Approach-RIMER , 2006, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans.

[17]  Xuan Li,et al.  Weapon System Capability Assessment under uncertainty based on the evidential reasoning approach , 2011, Expert Syst. Appl..

[18]  Weiru Liu,et al.  Analyzing the degree of conflict among belief functions , 2006, Artif. Intell..

[19]  Jian-Bo Yang,et al.  Rule and utility based evidential reasoning approach for multiattribute decision analysis under uncertainties , 2001, Eur. J. Oper. Res..

[20]  Linda Argote,et al.  Managing Knowledge in Organizations: An Integrative Framework and Review of Emerging Themes , 2003, Manag. Sci..

[21]  Jian-Bo Yang,et al.  Online updating belief rule based system for pipeline leak detection under expert intervention , 2009, Expert Syst. Appl..

[22]  Shanlin Yang,et al.  An attribute weight based feedback model for multiple attributive group decision analysis problems with group consensus requirements in evidential reasoning context , 2011, Eur. J. Oper. Res..

[23]  Jian-Bo Yang,et al.  A methodology to generate a belief rule base for customer perception risk analysis in new product development , 2011, Expert Syst. Appl..

[24]  Xiao-Sheng Si,et al.  On the dynamic evidential reasoning algorithm for fault prediction , 2011, Expert Syst. Appl..

[25]  Jian-Bo Yang,et al.  Integrated bank performance assessment and management planning using hybrid minimax reference point - DEA approach , 2010, Eur. J. Oper. Res..

[26]  Glenn Shafer,et al.  A Mathematical Theory of Evidence , 2020, A Mathematical Theory of Evidence.