EVALUATION OF TWO ARTIFICIAL NEURAL NETWORK SOFTWARE IN PREDICT OF CROP REFERENCE EVAPOTRANSPIRATION

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ZARE ABYANEH H.; GASEMI A.; BAYAT VARKESHI M.; MOHAMMADI K.; SABZIPARVAR A.A.

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Journal: WATER AND SOIL SCIENCE (AGRICULTURAL SCIENCE) Year:2010 | Volume:19.1 | Issue:2 Page(s): 201-212

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Title

EVALUATION OF TWO ARTIFICIAL NEURAL NETWORK SOFTWARE IN PREDICT OF CROP REFERENCE EVAPOTRANSPIRATION

Author(s)

Keywords

AIR TEMPERATUREQ4

ARTIFICIALQ3

NEURAL NETWORKSQ4

REFERENCE EVAPOTRANSPIRATIONQ2

RELATIVE HUMIDRTYQ2

Abstract

In this study, the performance of two different ARTIFICIAL neural network software's named neuro solution (NS) and neural works professional II (NW) in estimation of crop REFERENCE EVAPOTRANSPIRATION (ET0) were evaluated. For models evaluation, some statistical parameters such as root mean square error (RMSE), mean absolute error (MAE) and coefficient of determination (R2) were calculated for different arrays, learning rules and transfer functions. For the NS software the best fitted array characterizing with lowest values of RMSE, MAE and highest R2 were found to be 0.08, 0.07 (mm day-1) and 0.87, respectively. Results showed that the NS software with the best fitted network array of: learning rule of conjugate gradient and transfer function of sigmoid type, which required shorter computational time and less iteration loops, can perform better prediction. The results indicated that using two hidden layers did not improve the accuracy of ET0 predictions, in comparison with the results obtained by one hidden layer layout. The sensitivity analysis of neural network model revealed that ET0 is very sensitive to maximum AIR TEMPERATURE (Tmax). In contrast, the estimated daily ET0 showed the lowest sensitivity to minimum relative humidity (RHmin).

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APA: Copy

ZARE ABYANEH, H., GASEMI, A., BAYAT VARKESHI, M., MOHAMMADI, K., & SABZIPARVAR, A.A.. (2010). EVALUATION OF TWO ARTIFICIAL NEURAL NETWORK SOFTWARE IN PREDICT OF CROP REFERENCE EVAPOTRANSPIRATION. WATER AND SOIL SCIENCE (AGRICULTURAL SCIENCE), 19.1(2), 201-212. SID. https://sid.ir/paper/147826/en

Vancouver: Copy

ZARE ABYANEH H., GASEMI A., BAYAT VARKESHI M., MOHAMMADI K., SABZIPARVAR A.A.. EVALUATION OF TWO ARTIFICIAL NEURAL NETWORK SOFTWARE IN PREDICT OF CROP REFERENCE EVAPOTRANSPIRATION. WATER AND SOIL SCIENCE (AGRICULTURAL SCIENCE)[Internet]. 2010;19.1(2):201-212. Available from: https://sid.ir/paper/147826/en

IEEE: Copy

H. ZARE ABYANEH, A. GASEMI, M. BAYAT VARKESHI, K. MOHAMMADI, and A.A. SABZIPARVAR, “EVALUATION OF TWO ARTIFICIAL NEURAL NETWORK SOFTWARE IN PREDICT OF CROP REFERENCE EVAPOTRANSPIRATION,” WATER AND SOIL SCIENCE (AGRICULTURAL SCIENCE), vol. 19.1, no. 2, pp. 201–212, 2010, [Online]. Available: https://sid.ir/paper/147826/en

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