沈阳大学学报（自然科学版）2026，Vol.38Issue(4)：305-314,10.
基于多动量与区域加权机制的改进Adam优化算法
Improved Adam Optimization Algorithm Based on Multi-Momentum and Region Weighting Mechanism
摘要
Abstract
An improved Adam optimization algorithm named Improve-Adam was proposed,which introduced multiple momentum terms and a regional weighting mechanism to effectively enhance the convergence speed and performance stability during model training.Experimental results demonstrated that compared with the classic Adam algorithm,the Improve-Adam algorithm achieved higher accuracy in data classification.On the gastrointestinal disease dataset,the Improve-Adam algorithm attained accuracies of 77.60％and 75.60％on MobileNetV2 and ShuffleNetV2 networks,respectively.On the fundus glaucoma image dataset,it achieved accuracies of 84.79％and 84.60％on MobileNetV2 and ShuffleNetV2,respectively.关键词
深度学习/优化算法/区域加权机制/多动量法/改进Adam算法Key words
deep learning/optimization algorithm/regional weighting mechanism/multi-momentum strategy/improved Adam algorithm分类
信息技术与安全科学引用本文复制引用
邵一川,杨佳澎,周雯,张志涛,孙海静..基于多动量与区域加权机制的改进Adam优化算法[J].沈阳大学学报（自然科学版）,2026,38(4):305-314,10.基金项目
辽宁省教育厅高等学校基础研究项目(LJKZ0159) （LJKZ0159）
辽宁省教育厅基本科研项目(JYTMS20231160) （JYTMS20231160）
辽宁省教育科学"十四五"规划项目(JG22DB488). （JG22DB488）
