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Predicting Evaporation Using Optimized Multilayer Perceptron by Mohammad Ehteram; Akram Seifi; Fatemeh Barzegari Banadkooki is a book available to read on EtoBox.

What is Predicting Evaporation Using Optimized Multilayer Perceptron about?

In this study, the sunflower algorithm (SUA), shark algorithm (SHA), and particle swarm optimization (PASO) were integrated with the multilayer perceptron (MULP) model to predict daily evaporation. The average temperature (AVT), relative humidity (REH), wind speed (WISP), number of sunny hours (NSH), and rainfall (RAI) were used to predict evaporation at the Hormozgan, Fars, Mazandaran, Yazd, and Isfahan stations located in Iran country. The accuracy of the models indicated that the MULP-SUA provided the highest accuracy at the different stations. Also, the AVT and NSH were the most important parameters in desert climates. The results indicated that the optimized MULP models performed better than the MULP models.

Author

Mohammad Ehteram; Akram Seifi; Fatemeh Barzegari Banadkooki

Publisher

Springer Nature Singapore : Imprint: Springer

Published

2023

Language

EN

ISBN

9789811997334

Subjects

Science, Stem