{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,30]],"date-time":"2026-07-30T09:54:12Z","timestamp":1785405252676,"version":"3.56.0"},"reference-count":41,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2026,4,23]],"date-time":"2026-04-23T00:00:00Z","timestamp":1776902400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["22439001"],"award-info":[{"award-number":["22439001"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["22169006"],"award-info":[{"award-number":["22169006"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"award":["22439001"],"award-info":[{"award-number":["22439001"]}],"id":[{"id":"https:\/\/ror.org\/01h0zpd94","id-type":"ROR","asserted-by":"publisher"}]},{"award":["22169006"],"award-info":[{"award-number":["22169006"]}],"id":[{"id":"https:\/\/ror.org\/01h0zpd94","id-type":"ROR","asserted-by":"publisher"}]},{"DOI":"10.13039\/100012547","name":"Guangxi Natural Science Foundation Program","doi-asserted-by":"publisher","award":["2023AB01273"],"award-info":[{"award-number":["2023AB01273"]}],"id":[{"id":"10.13039\/100012547","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Guangxi Basic Ability Promotion Project for Young and Middle-aged Teachers","award":["2023KY0266"],"award-info":[{"award-number":["2023KY0266"]}]},{"name":"Guangxi Collaborative Innovation Center for New Energy and Materials Structure and Properties"},{"name":"Guilin University of Electronic Science and Technology"},{"id":[{"id":"https:\/\/ror.org\/05arjae42","id-type":"ROR","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Materials"],"abstract":"<jats:p>An accurate classification of material stability often requires fusing multiple features under uncertainty. Dempster\u2013Shafer (D\u2013S) theory is a powerful framework for multi-source information fusion under uncertainty. However, its effectiveness critically depends on the quality of basic probability assignments (BPAs), which are typically assigned heuristically. To overcome this limitation, we proposed a classification model that integrates genetic algorithm (GA)-optimized kernel density estimation (KDE) with a weighted D\u2013S fusion strategy. The GA automatically selects the optimal kernel function and bandwidth for KDE, enabling data-driven and accurate BPA construction without manual parameter tuning. The proposed method is first validated on benchmark datasets (Iris, Wine, Ionosphere, and Hepatitis), achieving competitive or superior performance compared to the existing methods. More importantly, when applied to predict the thermodynamic stability of double perovskite halide materials, our method achieves 93.7% accuracy and 85.3% precision under 10 \u00d7 five-fold cross-validation, substantially outperforming CatBC (76.9% precision) and XGBC (75.0% precision). Notably, the model maintains robust performance even for compositions containing chemical elements absent from the training set, demonstrating strong transferability. These results highlight the potential of our GA-KDE-DS framework as a practical tool for accelerating the discovery of novel functional materials under limited data and uncertain conditions.<\/jats:p>","DOI":"10.3390\/ma19091699","type":"journal-article","created":{"date-parts":[[2026,4,23]],"date-time":"2026-04-23T10:10:17Z","timestamp":1776939017000},"page":"1699","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A Genetic Algorithm-Optimized Kernel Density Estimation and D\u2013S Evidence Fusion Classification for Predicting the Stability of Double Perovskite Materials"],"prefix":"10.3390","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1289-2416","authenticated-orcid":false,"given":"Guiqin","family":"Liang","sequence":"first","affiliation":[{"name":"College of Information and Communication, Guilin University of Electronic Technology, Guilin 541004, China"},{"name":"College of Physics and Electronic Information Engineering, Guilin University of Technology, Guilin 541004, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jian","family":"Zhang","sequence":"additional","affiliation":[{"name":"College of Materials Science and Engineering, Guilin University of Electronic Technology, Guilin 541004, China"},{"name":"Guangxi Key Laboratory of Information Materials, Guangxi Collaborative Innovation Center of Structure and Property for New Energy and Materials, Guilin 541004, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,4,23]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"24","DOI":"10.1016\/j.cja.2023.12.009","article-title":"Multi-Source Information Fusion: Progress and Future","volume":"37","author":"Li","year":"2024","journal-title":"Chin. 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