Estimating evapotranspiration using neural networks and genetic algorithms (case study: Tabriz station)

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KHORSHID DOOST ALI MOHAMMAD; MIRHASHEMI HAMID; NAZARI MOUSA

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Journal: Journal of Geography and Planning Year:2019 | Volume:23 | Issue:68 Page(s): 71-90

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Information Journal Paper

Title

Estimating evapotranspiration using neural networks and genetic algorithms (case study: Tabriz station)

Author(s)

KHORSHID DOOST ALI MOHAMMAD | MIRHASHEMI HAMID | NAZARI MOUSA | Issue Writer Certificate

Keywords

Evaporation potentialQ2

Levenberg-MarquardtQ1

genetic algorithmsQ2

Neural NetworksQ2

Abstract

Evaporation is one of the important factors in the hydrological cycle and is one of the determinants of energy equilibrium at ground level and water balance, which is required in various areas such as hydrology, hydrology, agriculture, forest management, and management of water resources (Sanei Nejad et al., 2011). In this regard, one of the basic data in designing irrigation and drainage networks is the amount of evaporation power in each region. Because the design of transmission networks, such as drainage or drainage channels, as well as other parts of water design, depends on the amount of water required by the evaporation phenomenon (Jahanbakhsh et al., 1380). In general, evaporation hydrology is generally referred to as the phenomenon of water It simply turns steam into a physical process.

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APA: Copy

KHORSHID DOOST, ALI MOHAMMAD, MIRHASHEMI, HAMID, & NAZARI, MOUSA. (2019). Estimating evapotranspiration using neural networks and genetic algorithms (case study: Tabriz station). JOURNAL OF GEOGRAPHY AND PLANNING, 23(68 ), 71-90. SID. https://sid.ir/paper/359369/en

Vancouver: Copy

KHORSHID DOOST ALI MOHAMMAD, MIRHASHEMI HAMID, NAZARI MOUSA. Estimating evapotranspiration using neural networks and genetic algorithms (case study: Tabriz station). JOURNAL OF GEOGRAPHY AND PLANNING[Internet]. 2019;23(68 ):71-90. Available from: https://sid.ir/paper/359369/en

IEEE: Copy

ALI MOHAMMAD KHORSHID DOOST, HAMID MIRHASHEMI, and MOUSA NAZARI, “Estimating evapotranspiration using neural networks and genetic algorithms (case study: Tabriz station),” JOURNAL OF GEOGRAPHY AND PLANNING, vol. 23, no. 68 , pp. 71–90, 2019, [Online]. Available: https://sid.ir/paper/359369/en

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