{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,24]],"date-time":"2026-02-24T08:56:55Z","timestamp":1771923415474,"version":"3.50.1"},"reference-count":39,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2019,5,14]],"date-time":"2019-05-14T00:00:00Z","timestamp":1557792000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Entropy"],"abstract":"<jats:p>Uncertain information exists in each procedure of an air combat situation assessment. To address this issue, this paper proposes an improved method to address the uncertain information fusion of air combat situation assessment in the Dempster\u2013Shafer evidence theory (DST) framework. A better fusion result regarding the prediction of military intention can be helpful for decision-making in an air combat situation. To obtain a more accurate fusion result of situation assessment, an improved belief entropy (IBE) is applied to preprocess the uncertainty of situation assessment information. Data fusion of assessment information after preprocessing will be based on the classical Dempster\u2019s rule of combination. The illustrative example result validates the rationality and the effectiveness of the proposed method.<\/jats:p>","DOI":"10.3390\/e21050495","type":"journal-article","created":{"date-parts":[[2019,5,14]],"date-time":"2019-05-14T10:42:33Z","timestamp":1557830553000},"page":"495","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":18,"title":["A Novel Uncertainty Management Approach for Air Combat Situation Assessment Based on Improved Belief Entropy"],"prefix":"10.3390","volume":"21","author":[{"given":"Ying","family":"Zhou","sequence":"first","affiliation":[{"name":"School of Electronics and Information, Northwestern Polytechnical University, Xi\u2019an 710072, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2568-9628","authenticated-orcid":false,"given":"Yongchuan","family":"Tang","sequence":"additional","affiliation":[{"name":"School of Electronics and Information, Northwestern Polytechnical University, Xi\u2019an 710072, China"}]},{"given":"Xiaozhe","family":"Zhao","sequence":"additional","affiliation":[{"name":"School of Electronics and Information, Northwestern Polytechnical University, Xi\u2019an 710072, China"}]}],"member":"1968","published-online":{"date-parts":[[2019,5,14]]},"reference":[{"key":"ref_1","first-page":"2167-0374","article-title":"Genetic fuzzy based artificial intelligence for unmanned combat aerial vehicle control in simulated air combat missions","volume":"6","author":"Ernest","year":"2016","journal-title":"J. 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