Machine learning techniques to predict atmospheric black carbon in a tropical coastal environment-Reference-Cited by-同舟云学术

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Machine learning techniques to predict atmospheric black carbon in a tropical coastal environment

Published:2024-04 Issue: Volume:34 Page:101154
ISSN:2352-9385
Container-title:Remote Sensing Applications: Society and Environment
language:en
Short-container-title:Remote Sensing Applications: Society and Environment

Author:

Satpathy Priyadatta,Boopathy R.,Gogoi Mukunda M.,Suresh Babu S.,Das Trupti^ORCID

Funder

University Grants Commission

Institute of Minerals and Materials Technology

Indian Space Research Organisation

Publisher

Elsevier BV

Reference51 articles.

1. Comprehensive Action Plan for Clean Air for Non-attainment Cities of Odisha,2018

2. A long-term analysis of atmospheric black carbon MERRA-2 concentration over China during 1980–2019;Cao;Atmos. Environ.,2021

3. Artificial Intelligence-Based Solutions for Climate Change: a Review, Environmental Chemistry Letters;Chen,2023

4. Time series forecasting of temperatures using SARIMA: an example from nanjing;Chen;IOP Conf. Ser. Mater. Sci. Eng.,2018

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Estimating black carbon levels using machine learning models in high-concentration regions;Science of The Total Environment;2024-10

2. A GWO Optimized SVR for Time Series Prediction of Black Carbon across a Tropical Coastal Station in India;2024 3rd International Conference on Artificial Intelligence For Internet of Things (AIIoT);2024-05-03

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