Hakimi, Alireza, Monadjemi, S. Amirhassan, Setayeshi, Saeed. (1401). Modeling of the Earth’s rotation variations using a novel approach inspired by the brain emotional learning. نشریه مهندسی عمران امیرکبیر, 54(2), 173-184. doi: 10.22060/miscj.2023.21110.5271
Alireza Hakimi; S. Amirhassan Monadjemi; Saeed Setayeshi. "Modeling of the Earth’s rotation variations using a novel approach inspired by the brain emotional learning". نشریه مهندسی عمران امیرکبیر, 54, 2, 1401, 173-184. doi: 10.22060/miscj.2023.21110.5271
Hakimi, Alireza, Monadjemi, S. Amirhassan, Setayeshi, Saeed. (1401). 'Modeling of the Earth’s rotation variations using a novel approach inspired by the brain emotional learning', نشریه مهندسی عمران امیرکبیر, 54(2), pp. 173-184. doi: 10.22060/miscj.2023.21110.5271
Hakimi, Alireza, Monadjemi, S. Amirhassan, Setayeshi, Saeed. Modeling of the Earth’s rotation variations using a novel approach inspired by the brain emotional learning. نشریه مهندسی عمران امیرکبیر, 1401; 54(2): 173-184. doi: 10.22060/miscj.2023.21110.5271

Modeling of the Earth’s rotation variations using a novel approach inspired by the brain emotional learning

AUT Journal of Modeling and Simulation
مقاله 4، دوره 54، شماره 2، اسفند 2022، صفحه 173-184    اصل مقاله (718.53 K)
نوع مقاله: Research Article
شناسه دیجیتال (DOI): 10.22060/miscj.2023.21110.5271
نویسندگان
Alireza Hakimi1؛ S. Amirhassan Monadjemi2؛ Saeed Setayeshi* 3
1Department of AI, Faculty of Computer Engineering, University of Isfahan, Isfahan, Iran
2Department of Energy Engineering and Physics, Amirkabir University of Technology, Tehran, Iran
3School of Continuing and Lifelong Education, National University of Singapore, Singapore
چکیده
DT is a quantity that converts universal time (UT; defined by the Earth’s rotation) to terrestrial time (TT; independent of Earth’s rotation). The DT values during the time show the Earth’s rotation variations. Solar activities and the gravitational force of major solar system components are known as astronomical-based factors that can provide these variations. Recently, several models have been proposed to interpolate and forecast the DT values. Structurally, all mentioned methods have just used past DT values for modeling.
In this paper, we propose a novel approach for modeling DT based on the brain’s emotional learning with respect to astronomical-origin-based factors effective on the Earth’s rotation as the emotional input signals. This model, which employs memory units in the amygdala and orbitofrontal parts, can be named Memory-Based Brain Emotional Learning (MBBEL). MBBEL was run using the data from 1900 to 2000 and 2000 to 2019 as training and testing stages, respectively. After the modeling process, the mean absolute error (MSE) and maximum absolute error (MaxAE) of the train and test stages were 0.011, 0.051, 0.10, and 0.295, respectively. Comparing the MBBEL results against those of eight prior models revealed that MBBEL results considerably improved compared to those of the previous models.
کلیدواژه‌ها
DT؛ Time series؛ Brain emotional learning؛ Amygdala-Orbitofrontal System
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