物探与化探2025，Vol.49Issue(2)：259-269,11.DOI:10.11720/wtyht.2025.1391
基于深度兴趣演化网络的成矿预测
Metallogenic prediction based on the deep interest evolution network:A case study of supergenetic calcrete-hosted uranium deposits in Western Australia
摘要
Abstract
Recommendation system algorithms,having recently garnered significant attention in the field of digital Earth science,are expected to be widely applied in metallogenic prediction.Traditional metallogenic prediction studies fail to fully mine the various types of semantic information in massive geoscience data.The deep interest evolution network(DIEN),as a recommendation system algo-rithm,can fully mine semantic information to predict user preferences.Therefore,this study employed the DIEN model as the predic-tion model and the semantic information extracted from bedrock interpretation as the ore-controlling elements according to the database provided by the Western Australian government.The model was trained to perform metallogenic prediction for the study area.The pre-diction results indicate that 92.95%of uranium ore occurrences fell within the medium-high probability zone in the prediction map,with some unknown zones also showing high prediction probabilities.After removing known uranium ore occurrences in some zones,the retrained model still yielded medium-high prediction probabilities in these zones.The results suggest that the DIEN can effectively mine semantic information in metallogenic prediction studies,and the DIEN model exhibits strong predictive capacity for the study area,pro-viding a novel approach for metallogenic prediction studies.关键词
深度兴趣演化网络/成矿预测/语义信息/西澳大利亚/表生钙结岩型铀矿Key words
deep interest evolution network/metallogenic prediction/semantic information/Western Australia/supergenetic calcrete-hosted uranium deposit分类
天文与地球科学引用本文复制引用
张长江,何剑锋,聂逢君,夏菲,李卫东,汪雪元,张鑫,钟国韵..基于深度兴趣演化网络的成矿预测[J].物探与化探,2025,49(2):259-269,11.基金项目
国家自然科学基金项目(U2067202) （U2067202）
全国重点实验室基金项目(2024QZ-TD-10) （2024QZ-TD-10）
江西省主要学科学术和技术带头人培养计划项目(No.20225BCJ22004) （No.20225BCJ22004）
江西省重点研发计划项目(20203BBG73069) （20203BBG73069）
