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Title: Analysis of the memory mechanism in the pan evaporation phenomenon by the band similarity method
Authors: Yılmaz, Volkan
Keywords: Artificial bee colony
Band similarity
Support Vector Machine
Artificial Neural-Networks
Issue Date: 2023
Publisher: Springer Wien
Abstract: In this study, band similarity (BS) method as a new approach, which allows investigation of the memory features of the evaporation phenomenon, was applied on 7 different meteorological data in addition to the monthly pan evaporation data of Beysehir district of Konya city, located in the middle regions of Turkey. The models required for BS were generated with the artificial bee colony (ABC) optimization algorithm. As a result of the study, it has been observed that ABC optimization algorithm produced sufficient evaporation models. Subsequently, it was concluded that the BS method significantly improved the ABC results by using the temporal similarity mechanism. In this direction, it has been observed that the evaporation phenomenon studied remembers its own past. As a result of the BS method, it can be mentioned that there is a seasonal effect in the memory properties. While the memory weakens in the months when evaporation is high and low, it gets stronger especially in the spring and autumn months. Therefore, it has been concluded that the changes of the parameters affecting evaporation have a more intense effect on memory compared to their intensities. It is thought that this study differs from other studies in the literature because the pan evaporation phenomenon was evaluated from a different perspective and the BS method, which is a new method, and was applied for the first time on a hydrological parameter.
ISSN: 0177-798X
Appears in Collections:Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collections
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collections

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