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Information Journal Paper

Title

USING INTELLIGENCE MODELS TO ESTIMATE EVAPOTRANSPIRATION

Pages

  1-10

Abstract

 Exact estimation of EVAPOTRANSPIRATION is an important parameter in water cycle, study, design and management of irrigation systems. In this study, the efficiency of intelligent models such as FUZZY RULE BASE, FUZZY REGRESSION and ARTIFICIAL NEURAL NETWORKs for estimating daily EVAPOTRANSPIRATION has been examined and the results are compared to real data measured by lysimeter on the basis of a grass reference crop. Using daily climatic data from Ekbatan station in Hamadan in western Iran, including maximum and minimum temperatures, maximum and minimum relative humidities, wind speed and sunny hours, EVAPOTRANSPIRATION was estimated by the aforementioned intelligent models. The predicted EVAPOTRANSPIRATION values from FUZZY RULE BASE, fuzzy linear regression and ARTIFICIAL NEURAL NETWORK provided root mean square error (RMSE) of 0.72, 0.86 and 0.74 mm/day and determination coefficient (R2) of 0.88, 0.86 and 0.84, respectively. The FUZZY RULE BASE was hence found to be the most appropriate method employed for estimating EVAPOTRANSPIRATION.

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    APA: Copy

    SADATINEJAD, SEYED JAVAD, ANGABINI, SOMAYEH, & MOZDIAN FARD, MOHAMMADREZA. (2011). USING INTELLIGENCE MODELS TO ESTIMATE EVAPOTRANSPIRATION. ENVIRONMENTAL SCIENCES, 8(2), 1-10. SID. https://sid.ir/paper/117369/en

    Vancouver: Copy

    SADATINEJAD SEYED JAVAD, ANGABINI SOMAYEH, MOZDIAN FARD MOHAMMADREZA. USING INTELLIGENCE MODELS TO ESTIMATE EVAPOTRANSPIRATION. ENVIRONMENTAL SCIENCES[Internet]. 2011;8(2):1-10. Available from: https://sid.ir/paper/117369/en

    IEEE: Copy

    SEYED JAVAD SADATINEJAD, SOMAYEH ANGABINI, and MOHAMMADREZA MOZDIAN FARD, “USING INTELLIGENCE MODELS TO ESTIMATE EVAPOTRANSPIRATION,” ENVIRONMENTAL SCIENCES, vol. 8, no. 2, pp. 1–10, 2011, [Online]. Available: https://sid.ir/paper/117369/en

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