Feasibility of Random Forest and Multivariate Adaptive Regression Splines for Predicting Long-Term Mean Monthly Dew Point Temperature
- DOI
- 10.3389/fenvs.2022.826165
- Published
- 2022-04-04
- Container
- Frontiers in Environmental Science
- Publisher
- Frontiers Media SA
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.3389/fenvs.2022.826165,
title = {Feasibility of Random Forest and Multivariate Adaptive Regression Splines for Predicting Long-Term Mean Monthly Dew Point Temperature},
author = {Guodao Zhang and Sayed M. Bateni and Changhyun Jun and Helaleh Khoshkam and Shahab S. Band and Amir Mosavi},
year = {2022},
journal = {Frontiers in Environmental Science},
doi = {10.3389/fenvs.2022.826165},
url = {https://doi.org/10.3389/fenvs.2022.826165}
}RIS
TY - JOUR TI - Feasibility of Random Forest and Multivariate Adaptive Regression Splines for Predicting Long-Term Mean Monthly Dew Point Temperature AU - Guodao Zhang AU - Sayed M. Bateni AU - Changhyun Jun AU - Helaleh Khoshkam AU - Shahab S. Band AU - Amir Mosavi PY - 2022 JO - Frontiers in Environmental Science DO - 10.3389/fenvs.2022.826165 UR - https://doi.org/10.3389/fenvs.2022.826165 ER -
APA
Zhang, G., Bateni, S. M., Jun, C., Khoshkam, H., Band, S. S., & Mosavi, A. (2022). Feasibility of Random Forest and Multivariate Adaptive Regression Splines for Predicting Long-Term Mean Monthly Dew Point Temperature. Frontiers in Environmental Science. https://doi.org/10.3389/fenvs.2022.826165
Source records
- crossref · retrieved 2026-09-26T01:55:30.687Z