ESTIMATION OF DAILY POTENTIAL EVAPOTRANSPIRATION OF MEADOW USING ARTIFICIAL NEURAL NETWORKS

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SHAYANNEZHAD M.; SADATINEZHAD S.J.

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Journal: Journal of Rangeland Year:2008 | Volume:2 | Issue:2 Page(s): 182-194

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Information Journal Paper

Title

ESTIMATION OF DAILY POTENTIAL EVAPOTRANSPIRATION OF MEADOW USING ARTIFICIAL NEURAL NETWORKS

Author(s)

SHAYANNEZHAD M. | SADATINEZHAD S.J. | Issue Writer Certificate

Keywords

POTENTIAL EVAPOTRANSPIRATIONQ2

ARTIFICIAL NEURAL NETWORKSQ2

PENMAN-MONTEITHQ3

MEADOWQ2

Abstract

In this research the ability of ARTIFICIAL NEURAL NETWORKS (ANN) method was studied in estimation of daily POTENTIAL EVAPOTRANSPIRATION (ETp) of grass reference crop and then compared with PENMAN-MONTEITH method. We used clamatic data for a 5-years period of Ekbatan station in Hamadan. The input data for ANN were maximum and minimum temperature, maximum and minimum relative humidity, wind speed and sunny hours and ETp were set as output data. The best ANN architecturewas selected on the basis of minimizing the root mean square error (RMSE). The architecture of one hidden layer with one processing element gave the least RMSE of 0.7 mm/day and determinationco efficient of 0.84. Whereas, the RMSE and determination coefficient of Penman-Mantieth were 1.2 mm/day and 0.84 respectively. Based on these results, it could be concluded that the ANN predicted ETp better than Penman-Mantieth method. The sensitivity analysis also showed that the minimum temperature and maximum relative humidity had the most and the least effect on input respectively.

Cites

COMPARISON OF ARTIFICIAL NEURAL NETWORK AND MULTIVARIATE LINEAR REGRESSION (MLR) MODELS TO PREDICT COVER PERCENTAGE ARTEMISIA AUCHERI FROM SOME SOIL PROPERTIES

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APA: Copy

SHAYANNEZHAD, M., & SADATINEZHAD, S.J.. (2008). ESTIMATION OF DAILY POTENTIAL EVAPOTRANSPIRATION OF MEADOW USING ARTIFICIAL NEURAL NETWORKS. RANGELAND, 2(2), 182-194. SID. https://sid.ir/paper/136461/en

Vancouver: Copy

SHAYANNEZHAD M., SADATINEZHAD S.J.. ESTIMATION OF DAILY POTENTIAL EVAPOTRANSPIRATION OF MEADOW USING ARTIFICIAL NEURAL NETWORKS. RANGELAND[Internet]. 2008;2(2):182-194. Available from: https://sid.ir/paper/136461/en

IEEE: Copy

M. SHAYANNEZHAD, and S.J. SADATINEZHAD, “ESTIMATION OF DAILY POTENTIAL EVAPOTRANSPIRATION OF MEADOW USING ARTIFICIAL NEURAL NETWORKS,” RANGELAND, vol. 2, no. 2, pp. 182–194, 2008, [Online]. Available: https://sid.ir/paper/136461/en

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