Application of artificial intelligence in agrometeorology: a case study in Urmia Lake basin, Iran-Reference-Cited by-同舟云学术

Application of artificial intelligence in agrometeorology: a case study in Urmia Lake basin, Iran

Published:2022-05-31 Issue:3-4 Volume:149 Page:1195-1208
ISSN:0177-798X
Container-title:Theoretical and Applied Climatology
language:en
Short-container-title:Theor Appl Climatol

Author:

Faghih Homayoun^ORCID,Behmanesh Javad^ORCID,Rezaie Hossein^ORCID,Khalili Keivan^ORCID

Publisher

Springer Science and Business Media LLC

Subject

Atmospheric Science

Link

https://link.springer.com/content/pdf/10.1007/s00704-022-04104-6.pdf

Reference30 articles.

1. Adisa OM, Botai JO, Adeola AM, Hassen A, Botai CM, Darkey D, Tesfamariam E (2019) Application of artificial neural network for predicting maize production in South Africa. Sustainability 11(4):1145. https://doi.org/10.3390/su11041145

2. Arkian F, Nicholson SE, Ziaie B (2018) Meteorological factors affecting the sudden decline in Lake Urmia’s water level. Theoret Appl Climatol 131:641–651. https://doi.org/10.1007/s00704-016-1992-6

3. Bal S, Mukherjee J, Mallick K, Hundal SS (2004) Wheat yield forecasting models for Ludhiana district of Punjab state. Journal of Agrometeorology 6:161–165

4. Bowden P, Edwards J, Ferguson N, McNee T, Manning B, Roberts K et al. (2008) Wheat growth and development. Department of Primary Industries, New South Wales

5. Ceglar A, Toreti A, Lecerf R, Van der Velde M, Dentener F (2016) Impact of meteorological drivers on regional inter-annual crop yield variability in France. Agric for Meteorol 216:58–67

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