首都师范大学学报（自然科学版）2026，Vol.47Issue(2)：18-27,10.DOI:10.19789/j.1004-9398.2026.02.003
机器学习在环境科学与工程中的应用进展
Advances in the applications of machine learning in environmental science and engineering
摘要
Abstract
With the continuous advancement of environmental science and engineering,this field has increasingly entered the era of big data.As a pivotal branch of artificial intelligence,machine learning has been widely employed in environmental science and engineering owing to its superior capabilities in data processing and knowledge discovery.This review systematically examines the recent research progress and practical applications of machine learning in environmental science and engineering,encompassing diverse domains such as air pollution,water pollution,soil pollution,solid waste,noise pollution.The advantages and limitations of commonly used machine learning algorithms are comprehensively summarized.In addition,this paper discusses the existing challenges in current research and outlines prospects for future development.Among various algorithms,neural networks and random forests have gained significant traction due to their unique strengths and adaptability.Looking forward,the establishment of data and model sharing platforms,the development of ensemble learning approaches,and the integration of interdisciplinary technologies are identified as promising strategies to advance machine learning applications in environmental science and engineering.关键词
环境科学与工程/机器学习/集成学习Key words
environmental science and engineering/machine learning/ensemble learning分类
资源环境引用本文复制引用
张玉虎,李洁..机器学习在环境科学与工程中的应用进展[J].首都师范大学学报（自然科学版）,2026,47(2):18-27,10.基金项目
国家自然科学基金重点国际(地区)合作研究项目(42220104004) （地区）
国家重点研发计划项目(2023YFC3306400) （2023YFC3306400）
国家自然科学基金面上项目(42477440) （42477440）
