Surface Temperature Prediction Using Long Short-Term Memory – Case Study Java Island, Indonesia
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Department of Oceanography, Faculty of Fisheries and Marine Science, Diponegoro University, Jl. Prof. Sudarto No. 13, Tembalang, Kec. Tembalang, Kota Semarang, Java Tengah 50275, Indonesia
Corresponding author
Harmon Prayogi
Department of Oceanography, Faculty of Fisheries and Marine Science, Diponegoro University, Jl. Prof. Sudarto No. 13, Tembalang, Kec. Tembalang, Kota Semarang, Java Tengah 50275, Indonesia
Department of Oceanography, Faculty of Fisheries and Marine Science, Diponegoro University, Jl. Prof. Sudarto No. 13, Tembalang, Kec. Tembalang, Kota Semarang, Java Tengah 50275, Indonesia
Ecol. Eng. Environ. Technol. 2023; 4:73-78
KEYWORDS
TOPICS
Environmental monitoringClimate change in the environmentSimulations and computer modeling for the environment
ABSTRACT
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.
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