Used from Entropy theory and Gamma test in the determination input variables for daily evaporation estimation

Document Type : Research Article

Authors

1 water engineering department, Tabriz university, master student

2 water engineering department, Tabriz university,

3 tabriz university

Abstract

This research assessment ability of entropy theory and Gamma test for input variable of Artificial Network and Support Vector Machine as evaporation estimation for Rasht, Astara and Anzali in Guilan province. According the results, for Rasht synoptic, Astara and Anzali, Entropy Theory is determined that existence all variables are effective for modelling. Gamma test, for Rasht station two variables contain maximum and average humidity, for Anzali station three variables, contain minimum and average temperature and average humidity and for Astara station one variable contain wind speed eliminated form optimal composition. According to results two model’s Artificial Neural Network and Support Vector Machine performance have been acceptable. For determination of single input data in Rasht station Entropy Theory method and in the Anzali station Gamma test method have had good performance. For Astara station both of them have had good performance. Generally, according to the results, it can be said that Entropy theory had the stronger performance than Gamma test. But at the look of managerial, because the a few input variable selection than the Entropy theory, the Gamma performance has been acceptable than Entropy theory.

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References

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Iranian journal of Ecohydrology
Volume 5, Issue 2
July 2018
Pages 535-549

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History

  • Receive Date: 23 August 2017
  • Revise Date: 22 January 2018
  • Accept Date: 04 February 2018
  • First Publish Date: 22 June 2018
  • Publish Date: 22 June 2018

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