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Ehsanifar, Nohammad, Ehtesham Rasi, Reza. (1397). Evapotranspiration monthly using fuzzy neural network model and multiple regression model and comparing the results with real data of FAO Penman Monteith. , 53(1), 483-494. doi: 10.22059/jieng.2019.207333.1125
Nohammad Ehsanifar; Reza Ehtesham Rasi. "Evapotranspiration monthly using fuzzy neural network model and multiple regression model and comparing the results with real data of FAO Penman Monteith". , 53, 1, 1397, 483-494. doi: 10.22059/jieng.2019.207333.1125
Ehsanifar, Nohammad, Ehtesham Rasi, Reza. (1397). 'Evapotranspiration monthly using fuzzy neural network model and multiple regression model and comparing the results with real data of FAO Penman Monteith', , 53(1), pp. 483-494. doi: 10.22059/jieng.2019.207333.1125
Ehsanifar, Nohammad, Ehtesham Rasi, Reza. Evapotranspiration monthly using fuzzy neural network model and multiple regression model and comparing the results with real data of FAO Penman Monteith. , 1397; 53(1): 483-494. doi: 10.22059/jieng.2019.207333.1125

Evapotranspiration monthly using fuzzy neural network model and multiple regression model and comparing the results with real data of FAO Penman Monteith

Advances in Industrial Engineering
مقاله 2، دوره 53، شماره 1، فروردین 2019، صفحه 483-494    اصل مقاله (1.03 M)
نوع مقاله: Research Paper
شناسه دیجیتال (DOI): 10.22059/jieng.2019.207333.1125
نویسندگان
Nohammad Ehsanifar1؛ Reza Ehtesham Rasi* 2
1گروه مهندسی صنایع، واحد اراک، دانشگاه آزاد اسلامی، اراک، ایران
2گروه مدیریت صنعتی، واحد قزوین، دانشگاه آزاد اسلامی، قزوین
چکیده
In recent decades, due to the importance of the water issue and increased tendency to calculate the amount of runoff from precipitation, development and implementation of appropriate methods for predicting the precipitation of the data has become essential issue. Knowledge of evapotranspiration and crop water, forms the basis for a proper planning of irrigation-up. Without knowing the amount of water that the plants are or less of the water requirements of plants and reduce yields and cause other problems in agriculture or more of the required amount of plant and waste water and drainage issues such as drain.One of the most important ways to improve the management of water use, especially in agriculture, the major share of water consumption in the country. Precise estimates of water use, which directly depends on the "ET " in plants. The evapotranspiration due to the application of proper management is inevitable water resources. There are many ways to predict evapotranspiration of the reference can be cited methods FAO Penman-Monteith method. Several research is in this field within the country that most of these predictions have been based on empirical methods and new methods have been used less. This research aims to predict the results of the two methods using artificial neural networks and regression trees to predict paid evapotranspiration and as well as to assess the effectiveness of its common Forecast.
کلیدواژه‌ها
Prediction evapotranspiration؛ Fuzzy Network؛ Regression tree؛ Water management
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