Estimating evapotranspiration using neural networks and genetic algorithms (case study:Tabriz station)
| Autor: | Ali Mohammad Khrshieddoust, Hamid Mirhashemi, Mousa Nazari |
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| Jazyk: | perština |
| Rok vydání: | 2019 |
| Předmět: | |
| Zdroj: | نشریه جغرافیا و برنامهریزی, Vol 23, Iss 68, Pp 71-90 (2019) |
| Druh dokumentu: | article |
| ISSN: | 2008-8078 2717-3534 |
| Popis: | 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. |
| Databáze: | Directory of Open Access Journals |
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