LSTM-Powered COVID-19 prediction in central Thailand incorporating meteorological and particulate matter data with a multi-feature selection approach.
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| Title: | LSTM-Powered COVID-19 prediction in central Thailand incorporating meteorological and particulate matter data with a multi-feature selection approach. |
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| Authors: | Winalai C; Department of Physics, Faculty of Science, Naresuan University, Phitsanulok 65000, Thailand., Anupong S; Department of Chemistry, Mahidol Wittayanusorn School (MWIT), Salaya, Nakhon Pathom 73170, Thailand., Modchang C; Biophysics Group, Department of Physics, Faculty of Science, Mahidol University, Bangkok 10400, Thailand.; Centre of Excellence in Mathematics, CHE, Bangkok 10400, Thailand.; Thailand Center of Excellence in Physics, CHE, 328 Si Ayutthaya Road, Bangkok 10400, Thailand., Chadsuthi S; Department of Physics, Faculty of Science, Naresuan University, Phitsanulok 65000, Thailand. |
| Source: | Heliyon [Heliyon] 2024 Apr 26; Vol. 10 (9), pp. e30319. Date of Electronic Publication: 2024 Apr 26 (Print Publication: 2024). |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Elsevier Ltd Country of Publication: England NLM ID: 101672560 Publication Model: eCollection Cited Medium: Print ISSN: 2405-8440 (Print) Linking ISSN: 24058440 NLM ISO Abbreviation: Heliyon Subsets: PubMed not MEDLINE |
| Database: | MEDLINE Ultimate |
| ISSN: | 2405-8440 |
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| DOI: | 10.1016/j.heliyon.2024.e30319 |
