Project management: using fuzzy logic and the Dempster-Shafer theory of evidence to select team members for the project duration

This research aims to combine the mathematical theory of evidence with the rule based logics to refine the predictable output. Integrating Fuzzy Logic and Dempster-Shafer theory by calculating the similarity between Fuzzy membership function. The novelty aspect of this work is that basic probability assignment is proposed based on the similarity measure between membership function. The similarity between Fuzzy membership function is calculated to get a basic probability assignment. The Dempster-Shafer mathematical theory of evidence has attracted considerable attention as a promising method of dealing with some of the basic problems arising in combination of evidence and data fusion. Dempster-Shafer theory provides the ability to deal with ignorance and missing information. The foundation of Fuzzy logic is natural language which can help to make full use of expert information.

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An Improved Algorithm for Dempster-Shafer Theory of Evidence

2009 International Conference on Electronic Commerce and Business Intelligence ◽

10.1109/ecbi.2009.44 ◽

2009 ◽

Cited By ~ 3

Author(s):

Yan Chenghua ◽

Chen Qixiang

Keyword(s):

Dempster Shafer Theory ◽

Shafer Theory ◽

Theory Of Evidence ◽

Improved Algorithm

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Maintenance policy performance assessment in presence of imprecision based on Dempster–Shafer Theory of Evidence

Information Sciences ◽

10.1016/j.ins.2012.11.003 ◽

2013 ◽

Vol 245 ◽

pp. 112-131 ◽

Cited By ~ 30

Author(s):

P. Baraldi ◽

M. Compare ◽

E. Zio

Keyword(s):

Performance Assessment ◽

Maintenance Policy ◽

Policy Performance ◽

Dempster Shafer Theory ◽

Shafer Theory ◽

Theory Of Evidence

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A MODIFIED D NUMBERS METHODOLOGY FOR ENVIRONMENTAL IMPACT ASSESSMENT

Technological and Economic Development of Economy ◽

10.3846/20294913.2016.1216018 ◽

2017 ◽

Vol 24 (2) ◽

pp. 653-669 ◽

Cited By ~ 10

Author(s):

Ningkui WANG ◽

Daijun WEI

Keyword(s):

Environmental Impact ◽

Impact Assessment ◽

Environmental Impact Assessment ◽

Previous Method ◽

Combination Process ◽

Dempster Shafer Theory ◽

Shafer Theory ◽

Theory Of Evidence ◽

D Numbers ◽

Commutative Property

Environmental impact assessment (EIA) is usually evaluated by many factors influenced by various kinds of uncertainty or fuzziness. As a result, the key issues of EIA problem are to represent and deal with the uncertain or fuzzy information. D numbers theory, as the extension of Dempster-Shafer theory of evidence, is a desirable tool that can express uncertainty and fuzziness, both complete and incomplete, quantitative or qualitative. However, some shortcomings do exist in D numbers combination process, the commutative property is not well considered when multiple D numbers are combined. Though some attempts have made to solve this problem, the previous method is not appropriate and convenience as more information about the given evaluations represented by D numbers are needed. In this paper, a data-driven D numbers combination rule is proposed, commutative property is well considered in the proposed method. In the combination process, there does not require any new information except the original D numbers. An illustrative example is provided to demonstrate the effectiveness of the method.

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