Essential Conflict Measurement in Dempster–Shafer Theory for Intelligent Information Fusion

Ma, Wenjun; He, Meishen; Wang, Siyuan; Zhan, Jieyu

doi:10.3390/math14010097

Open AccessFeature PaperArticle

Essential Conflict Measurement in Dempster–Shafer Theory for Intelligent Information Fusion

by

Wenjun Ma

^1,2,†,

Meishen He

^3,†,

Siyuan Wang

¹

and

Jieyu Zhan

^1,*

¹

School of Computer Science, South China Normal University, Guangzhou 510631, China

²

Aberdeen Institute of Data Science and Artificial Intelligence, South China Normal University, Guangzhou 510631, China

³

School of Artificial Intelligence, South China Normal University, Foshan 528225, China

^*

Author to whom correspondence should be addressed.

^†

These authors contributed equally to this work.

Mathematics 2026, 14(1), 97; https://doi.org/10.3390/math14010097

Submission received: 19 November 2025 / Revised: 22 December 2025 / Accepted: 25 December 2025 / Published: 26 December 2025

(This article belongs to the Special Issue Deep Learning Algorithms and Game Theory Models for Intelligent Information Processing and Decision-Making)

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Abstract

Dempster’s combination rule in Dempster–Shafer theory is a powerful and effective tool for multi-sensor data fusion. However, counterintuitive results are possible under the condition of a high conflict between pieces of evidence. This study demonstrates that existing conflict measurements cannot prevent such results and, thus, proposes a quantitative conflict measurement based on the concept of essential conflict. This work analyzes two characteristics of the essential conflict, namely belief absolutization and uncorrectable assertions. In addition, considering the desirable properties of the measurement, this study demonstrates that the measurement of essential conflict can reveal the essence of counterintuitive results in Dempster’s combination process. Finally, properties and examples are used to validate the proposed measurement.

Keywords: information fusion; D-S theory of evidence; conflict management; essential conflict; counterintuitive combination result

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MDPI and ACS Style

Ma, W.; He, M.; Wang, S.; Zhan, J. Essential Conflict Measurement in Dempster–Shafer Theory for Intelligent Information Fusion. Mathematics 2026, 14, 97. https://doi.org/10.3390/math14010097

AMA Style

Ma W, He M, Wang S, Zhan J. Essential Conflict Measurement in Dempster–Shafer Theory for Intelligent Information Fusion. Mathematics. 2026; 14(1):97. https://doi.org/10.3390/math14010097

Chicago/Turabian Style

Ma, Wenjun, Meishen He, Siyuan Wang, and Jieyu Zhan. 2026. "Essential Conflict Measurement in Dempster–Shafer Theory for Intelligent Information Fusion" Mathematics 14, no. 1: 97. https://doi.org/10.3390/math14010097

APA Style

Ma, W., He, M., Wang, S., & Zhan, J. (2026). Essential Conflict Measurement in Dempster–Shafer Theory for Intelligent Information Fusion. Mathematics, 14(1), 97. https://doi.org/10.3390/math14010097

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

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Essential Conflict Measurement in Dempster–Shafer Theory for Intelligent Information Fusion

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