Machine learning algorithms for high-resolution prediction of spatiotemporal distribution of air pollution from meteorological and soil parameters
This study uses machine learning (ML) models for a high-resolution prediction (0.1°×0.1°) of air fine particular matter (PM2.5) concentration, the most harmful to human health, from meteorological and soil data. Iraq was considered the study area to implement the method. Different lags and the chang...
| 出版年: | Environment International |
|---|---|
| 第一著者: | |
| フォーマット: | 論文 |
| 言語: | English |
| 出版事項: |
Elsevier Ltd
2023
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| オンライン･アクセス: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85153537218&doi=10.1016%2fj.envint.2023.107931&partnerID=40&md5=91f7aa5b1ffbb13a2eae2389f70ff7ea |