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Estimating Reference Evapo- transpiration in Mosul (Iraq) Using Cascade Neural Networks | ||
| Engineering and Technology Journal | ||
| Article 14, Volume 32, Issue 9, 2014, Pages 2277-2285 PDF (450.98 K) | ||
| DOI: 10.30684/etj.32.9A14 | ||
| Authors | ||
| Fatin Mahmoud Shehab; Raid Rafi Omar; Radhwan Yousif Sedik | ||
| Abstract | ||
| Recently artificial neural network (ANN) has been applied for estimating reference evapo-transpiration (ETₒ).In this study a mathematical model was built by application the cascade forward network technique (CCANN) to estimate the daily reference evapo-transpiration in the city of Mosul, north of Iraq .The input parameters for the CCANN were the: temperature, solar radiation, wind speed at 2m height, and relative humidity. A check for the accuracy of the performance of the network was made using values of reference evapo-transpiration obtained from pan evaporation method. The results revealed linear correlation between the network output and the data of the measured pan evapo-transpiration with correlation coefficient of (0.9679). This indicates the possibility of use of CCANN to determine the daily reference evapo- transpiration. The results also show that the CCANN model performs better more accurate compared to other models. | ||
| Keywords | ||
| evapo; transpiration; cascade; neural network | ||
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