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Effective Analysis of Human Exposure Conditions with Body-worn Dosimeters in the 2.4 GHz Band
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Probabilistic Hesitant Fuzzy Evidence Theory and Its Application in Capability Evaluation of a Satellite
Jiahuan Liu1, Ping Jian1, Desheng Liu1
1Science and Technology on Complex Electronic System Simulation Laboratory, Space Engineering University, Beijing 101400, China.
Entropy (Basel, Switzerland)
|January 26, 2024
Summary
This study introduces probabilistic hesitant fuzzy evidence theory (PHFET) to evaluate satellite communication system (SCS) capabilities. PHFET effectively handles ambiguous data for improved system evaluation.
Area of Science:
- Information Fusion
- Artificial Intelligence
- Communication Systems Engineering
Background:
- Evaluating satellite communication system (SCS) capabilities is complex and ambiguous.
- Uncertainty in data hinders accurate analysis and expert judgment for SCS evaluation.
- Existing methods struggle with ambiguous, multi-source information in SCS assessments.
Purpose of the Study:
- To propose an innovative approach for evaluating SCS capabilities using extended Dempster-Shafer theory.
- To introduce probabilistic hesitant fuzzy evidence theory (PHFET) to manage uncertainty and ambiguity.
- To develop a robust model for assessing SCS capability requirement satisfaction.
Main Methods:
- Extended Dempster-Shafer theory (DST) to probabilistic hesitant fuzzy evidence theory (PHFET).
- Introduced probabilistic hesitant fuzzy basic probability assignment (PHFBPA) for measuring support.
- Developed PHFBPA generation methods (multi-classifier, distance) and discounting factors (entropy, Jousselme distance).
Main Results:
- Demonstrated the effectiveness and stability of the PHFET method through experimental classification and evaluation.
- PHFET successfully handled ambiguous data in multi-source information fusion for SCS capability assessment.
- Improved consistency of evidence through proposed discounting factors.
Conclusions:
- PHFET offers a compelling solution for evaluating SCS capabilities in uncertain environments.
- The proposed approach enhances multi-source information fusion by effectively managing ambiguous data.
- This work advances the field of evidence theory for complex system evaluations.
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