Dempster-Shafer theory of evidence: A new approach to spatially model wildfire risk potential in central Chile

In this paper, we develop a new approach for decision making with Dempster-Shafer theory of evidence by using linguistic information. We suggest the use of different types of linguistic aggregation operators in the model. We then obtain as a result, the belief structure — linguistic ordered weighted averaging (BS-LOWA), the BS — linguistic hybrid averaging (BS-LHA) and a wide range of particular cases. Some of their main properties are studied. Finally, we provide an illustrative example that shows the different results obtained by using different types of linguistic aggregation operators in the new approach.

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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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