A smart IoT-based irrigation system design using AI and prediction model

Author:

Behzadipour Faeze,Ghasemi Nezhad Raeini Mahmod,Abdanan Mehdizadeh SamanORCID,Taki Morteza,Khalil Moghadam Bijan,Zare Bavani Mohammad Reza,Lloret Jaime

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Software

Reference42 articles.

1. Ashofteh PA, Bozorg-Haddad O, Loáiciga HA (2019) Application of bi-objective genetic programming (BO-GP) for optimizing irrigation rules using two reservoir performance criteria. Int J River Basin Manage 19:1–35. https://doi.org/10.1080/15715124.2019.1613415

2. Baaghideh M, Entezari A, Kordi A (2019) Investigation of the relationship between soil temperature and climate parameters in the Northwest of Iran (1992–2015). J Geogr Reg Dev Res 16(1):279–307

3. Bagheri N (2019) Information technology is an infrastructure for the development of intelligent agriculture. Agri Inf Sci Technol 2(1):35–49 ((In Farsi))

4. Barikloo A, Alamdari P, Moravej K, Servati M (2017) Prediction of irrigated Wheat yield by using hybrid algorithm methods of artificial neural networks and genetic algorithm. J Water Soil 31(3):715–726

5. Behmann J, Steinrücken J, Plümer L (2014) Detection of early plant stress responses in hyperspectral images. J Int Soc Photogramm Remote Sensing (ISPRS) 93:98–111. https://doi.org/10.1016/j.isprsjprs.2014.03.016

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