Surface Temperature Prediction Using Long Short-Term Memory – Case Study Java Island, Indonesia

• Autorzy: Satriadi Alfi , Widada Sugeng , Prayogi Harmon

Identyfikatory

DOI

10.12912/27197050/161962

• Języki publikacji: EN

Abstrakty

EN

We predict the surface temperature of Java Island in Indonesia based on a dataset of wind speed, surface temperature, and surface pressure from 2002 to 2021. Long short-term memory model is employed to predict the surface temperature in 2022. The predicted surface temperature corresponds to the seasons of Indonesia. The result shows a pattern between dry and monsoon seasons of Indonesia. The performance of the model is evaluated using root mean square error. The root mean square error in the land area is larger than the water area.

Słowa kluczowe

EN

long short-term memory; wind speed; surface temperature; surface pressure; Hovmöller diagram

• Wydawca: Lubelski Oddział Polskiego Towarzystwo Inżynierii Ekologicznej ; Lublin University of Technology ; WNGB Wydawnictwo Naukowe
• Czasopismo: Ecological Engineering & Environmental Technology
• Rocznik: 2023
• Tom: Vol. 24, iss. 4
• Strony: 73--78
• Opis fizyczny: Bibliogr. 20 poz., rys.

Twórcy

autor

Satriadi Alfi

• Department of Oceanography, Faculty of Fisheries and Marine Science, Diponegoro University, Jl. Prof. Sudarto No. 13, Tembalang, Kec. Tembalang, Kota Semarang, Jawa Tengah 50275, Indonesia

• https://orcid.org/0000-0002-4805-6316

autor

Widada Sugeng

• Department of Oceanography, Faculty of Fisheries and Marine Science, Diponegoro University, Jl. Prof. Sudarto No. 13, Tembalang, Kec. Tembalang, Kota Semarang, Jawa Tengah 50275, Indonesia

• https://orcid.org/0000-0002-7609-4950

autor

Prayogi Harmon

• Department of Oceanography, Faculty of Fisheries and Marine Science, Diponegoro University, Jl. Prof. Sudarto No. 13, Tembalang, Kec. Tembalang, Kota Semarang, Jawa Tengah 50275, Indonesia

• https://orcid.org/0000-0002-2806-3578

Bibliografia

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Uwagi

Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).