An improved model based on the support vector machine and cuckoo algorithm for simulating reference evapotranspiration

article; evapotranspiration; fuzzy system; genetic model; humidity; India; simulation; support vector machine; wind speed; environmental monitoring; fuzzy logic; irrigation (agriculture); procedures; river; support vector machine; temperature; wind; Agricultural Irrigation; Environmental Monitoring;...

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Main Authors: Ehteram M., Singh V.P., Ferdowsi A., Mousavi S.F., Farzin S., Karami H., Mohd N.S., Afan H.A., Lai S.H., Kisi O., Malek M.A., Ahmed A.N., El-Shafie A.
Other Authors: 57113510800
Format: Article
Published: Public Library of Science 2023
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Institution: Universiti Tenaga Nasional
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spelling my.uniten.dspace-246812023-05-29T15:25:48Z An improved model based on the support vector machine and cuckoo algorithm for simulating reference evapotranspiration Ehteram M. Singh V.P. Ferdowsi A. Mousavi S.F. Farzin S. Karami H. Mohd N.S. Afan H.A. Lai S.H. Kisi O. Malek M.A. Ahmed A.N. El-Shafie A. 57113510800 57211219633 57207964868 7003344568 55315758000 36863982200 57192892703 56436626600 36102664300 6507051085 55636320055 57214837520 16068189400 article; evapotranspiration; fuzzy system; genetic model; humidity; India; simulation; support vector machine; wind speed; environmental monitoring; fuzzy logic; irrigation (agriculture); procedures; river; support vector machine; temperature; wind; Agricultural Irrigation; Environmental Monitoring; Fuzzy Logic; Rivers; Support Vector Machine; Temperature; Wind Reference evapotranspiration (ET0) plays a fundamental role in irrigated agriculture. The objective of this study is to simulate monthly ET0 at a meteorological station in India using a new method, an improved support vector machine (SVM) based on the cuckoo algorithm (CA), which is known as SVM-CA. Maximum temperature, minimum temperature, relative humidity, wind speed and sunshine hours were selected as inputs for the models used in the simulation. The results of the simulation using SVM-CA were compared with those from experimental models, genetic programming (GP), model tree (M5T) and the adaptive neuro-fuzzy inference system (ANFIS). The achieved results demonstrate that the proposed SVM-CA model is able to simulate ET0 more accurately than the GP, M5T and ANFIS models. Two major indicators, namely, root mean square error (RMSE) and mean absolute error (MAE), indicated that the SVM-CA outperformed the other methods with respective reductions of 5-15% and 5-17% compared with the GP model, 12-21% and 10-22% compared with the M5T model, and 7-15% and 5-18% compared with the ANFIS model, respectively. Therefore, the proposed SVM-CA model has high potential for accurate simulation of monthly ET0 values compared with the other models. � 2019 Ehteram et al. Final 2023-05-29T07:25:48Z 2023-05-29T07:25:48Z 2019 Article 10.1371/journal.pone.0217499 2-s2.0-85066480927 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85066480927&doi=10.1371%2fjournal.pone.0217499&partnerID=40&md5=bd9885bb83bc7c1294d98b023cf42e54 https://irepository.uniten.edu.my/handle/123456789/24681 14 5 e0217499 All Open Access, Gold, Green Public Library of Science Scopus
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
description article; evapotranspiration; fuzzy system; genetic model; humidity; India; simulation; support vector machine; wind speed; environmental monitoring; fuzzy logic; irrigation (agriculture); procedures; river; support vector machine; temperature; wind; Agricultural Irrigation; Environmental Monitoring; Fuzzy Logic; Rivers; Support Vector Machine; Temperature; Wind
author2 57113510800
author_facet 57113510800
Ehteram M.
Singh V.P.
Ferdowsi A.
Mousavi S.F.
Farzin S.
Karami H.
Mohd N.S.
Afan H.A.
Lai S.H.
Kisi O.
Malek M.A.
Ahmed A.N.
El-Shafie A.
format Article
author Ehteram M.
Singh V.P.
Ferdowsi A.
Mousavi S.F.
Farzin S.
Karami H.
Mohd N.S.
Afan H.A.
Lai S.H.
Kisi O.
Malek M.A.
Ahmed A.N.
El-Shafie A.
spellingShingle Ehteram M.
Singh V.P.
Ferdowsi A.
Mousavi S.F.
Farzin S.
Karami H.
Mohd N.S.
Afan H.A.
Lai S.H.
Kisi O.
Malek M.A.
Ahmed A.N.
El-Shafie A.
An improved model based on the support vector machine and cuckoo algorithm for simulating reference evapotranspiration
author_sort Ehteram M.
title An improved model based on the support vector machine and cuckoo algorithm for simulating reference evapotranspiration
title_short An improved model based on the support vector machine and cuckoo algorithm for simulating reference evapotranspiration
title_full An improved model based on the support vector machine and cuckoo algorithm for simulating reference evapotranspiration
title_fullStr An improved model based on the support vector machine and cuckoo algorithm for simulating reference evapotranspiration
title_full_unstemmed An improved model based on the support vector machine and cuckoo algorithm for simulating reference evapotranspiration
title_sort improved model based on the support vector machine and cuckoo algorithm for simulating reference evapotranspiration
publisher Public Library of Science
publishDate 2023
_version_ 1806427740563308544