机器学习在淡水系统有机物和有害藻华中的实际应用综述

IF 11.4 1区 环境科学与生态学 Q1 ENVIRONMENTAL SCIENCES
Xuan Cuong Nguyen, Vu Khac Hoang Bui, Kyung Hwa Cho, Jin Hur
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引用次数: 0

摘要

机器学习(ML)技术在理解和预测淡水系统中有机物(OM)和有害藻华(HABs)方面的应用随着气候变化而显著增加。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Practical application of machine learning for organic matter and harmful algal blooms in freshwater systems: A review
The application of machine learning (ML) techniques for understanding and predicting organic matter (OM) and harmful algal blooms (HABs) in freshwater systems has increased significantly with the a...
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来源期刊
CiteScore
27.30
自引率
1.60%
发文量
64
审稿时长
2 months
期刊介绍: Two of the most pressing global challenges of our era involve understanding and addressing the multitude of environmental problems we face. In order to tackle them effectively, it is essential to devise logical strategies and methods for their control. Critical Reviews in Environmental Science and Technology serves as a valuable international platform for the comprehensive assessment of current knowledge across a wide range of environmental science topics. Environmental science is a field that encompasses the intricate and fluid interactions between various scientific disciplines. These include earth and agricultural sciences, chemistry, biology, medicine, and engineering. Furthermore, new disciplines such as environmental toxicology and risk assessment have emerged in response to the increasing complexity of environmental challenges. The purpose of Critical Reviews in Environmental Science and Technology is to provide a space for critical analysis and evaluation of existing knowledge in environmental science. By doing so, it encourages the advancement of our understanding and the development of effective solutions. This journal plays a crucial role in fostering international cooperation and collaboration in addressing the pressing environmental issues of our time.
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