Artificial neural network–genetic algorithm for estimation of crop evapotranspiration in a semi-arid region of Iran

Author:

Aghajanloo Mohammad-Bagher,Sabziparvar Ali-Akbar,Hosseinzadeh Talaee P.

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Software

Reference38 articles.

1. Alizadeh A (2005) Principles of applied hydrology. Astan Ghods Razavi Press, Mashhad (in Persian)

2. Allen RG, Periera LS, Raes D, Smith M (1998) Crop evapotranspiration: guideline for computing crop water requirement. FAO Irrigation and Drainage Paper No. 56. Food and Agriculture Organization of the UN, Rome, p 301

3. Beale R, Jackson T (1991) Neural computing: an introduction. Adam Hilger, Techno House

4. Chauhan S, Shrivastava RK (2009) Performance evaluation of reference evapotranspiration estimation using climate based methods and artificial neural networks. Water Resour Manage 23(5):825–837

5. Curry B, Morgan P, Silver M (2002) Neural networks and non-linear statistical methods: an application to the modeling of price-quality relationships. Comput Oper Res 29:951–969

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