Comparison and evaluation of machine learning approaches for estimating heat index map in Türkiye
Author:
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Software
Link
https://link.springer.com/content/pdf/10.1007/s00521-023-08578-x.pdf
Reference50 articles.
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2. Zune M, Rodrigues L, Gillott M (2020) The vulnerability of homes to overheating in Myanmar today and in the future: a heat index analysis of measured and simulated data. Energy Build 223:110201. https://doi.org/10.1016/j.enbuild.2020.110201
3. TSMS (2022) Real feel temperature. https://www.mgm.gov.tr/
4. Steadman RG (1979) The assessment of sultriness. Part I: a temperature-humidity index based on human physiology and clothing science. J Appl Meteorol 18:861–873. https://doi.org/10.1175/1520-0450(1979)018%3c0861:taospi%3e2.0.co;2
5. Steadman RG (1979) The assessment of sultriness. Part II: effects of wind, extra radiation and barometric pressure on apparent temperature. J Appl Meteorol 18:874–885. https://doi.org/10.1175/1520-0450(1979)018%3c0874:taospi%3e2.0.co;2
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