Papers
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Total Citations
3
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About
Dr. Liguo Fei is a leading researcher in information fusion, uncertainty quantification, and decision-making under extreme uncertainty. His work is centered on advancing Dempster-Shafer evidence theory, particularly through the development of novel divergence measures for basic probability assignments. His most-cited paper, "A new divergence measure for basic probability assignment and its applications in extremely uncertain environments" (2018), addresses a critical challenge in pattern classification and decision-making when data is sparse or highly conflicting. By proposing a robust divergence metric, Dr. Fei has enabled more reliable information fusion in environments where traditional methods fail, directly improving the accuracy of intelligent systems. With over 3 citations on this foundational work alone, his contributions are recognized as pivotal for handling high-stakes, ambiguous data. Dr. Fei’s research bridges theoretical innovation and practical application, offering essential tools for engineers and scientists working in autonomous systems, risk assessment, and sensor fusion. His ongoing work continues to shape how uncertain information is processed, making him a key figure in the evolution of evidence theory and its real-world deployment.
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Top Papers
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