Interval-valued belief entropies for Dempster-Shafer structures
1Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, Chengdu, 610054 China.
Soft Computing
|June 9, 2021
Summary
This study introduces interval-valued belief entropies for Dempster-Shafer structures, extending existing models to handle uncertainty in evidential environments. This new method effectively quantifies uncertainty for better decision-making.
Area of Science:
- Uncertainty Quantification
- Information Theory
- Decision Theory
Background:
- Traditional entropy models struggle with complex uncertainty in practical applications.
- Yager's interval-valued entropies for Dempster-Shafer structures offer a solution within traditional probability spaces.
- Extending these entropies to broader evidential environments remains an open challenge.
Purpose of the Study:
- To propose and validate interval-valued belief entropies for Dempster-Shafer structures.
- To extend the applicability of interval entropy models to evidential reasoning.
- To provide a robust method for quantifying uncertainty in complex scenarios.
Main Methods:
- Development of interval-valued belief entropies based on Dempster-Shafer structures.
- Mathematical formulation ensuring degeneracy to interval-valued entropies under specific conditions.
- Application of numerical examples to demonstrate validity and effectiveness.
Main Results:
- The proposed interval-valued belief entropies successfully quantify the interval uncertainty of objects.
- The method is shown to be effective in decision-making processes.
- Validation through numerical examples confirms the theoretical framework.
Conclusions:
- Interval-valued belief entropies offer a significant advancement for uncertainty quantification in evidential environments.
- This approach enhances the practical utility of Dempster-Shafer structures.
- The findings support improved theoretical research and industrial applications involving complex uncertainty.
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