Sunspot number prediction using Gated Recurrent Unit (GRU) algorithm

Arfianti, Unix Izyah and Novitasari, Dian Candra Rini and Widodo, Nanang and Hafiyusholeh, Moh. and Utami, Wika Dianita (2021) Sunspot number prediction using Gated Recurrent Unit (GRU) algorithm. IJCCS (Indonesian Journal of Computing and Cybernetics Systems), 15 (2). pp. 141-152. ISSN 1978-1520; 2460-7258

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Sunspot is an area on photosphere layer which is dark-colored. Sunspot is very important to be researched because sunspot is affected by sunspot numbers, which present the level of solar activity. This research was conducted to make prediction on sunspot numbers using Gated Recurrent Unit (GRU) algorithm. The work principle of GRU is similar to Long short-term Memory (LSTM) method: the information from the previous memory is processed through two gates, that is update gate and reset gate, then the output generated will be input for the next process. The purpose of predicting sunspot numbers was to find out the information of sunspot numbers in the future, so that if there is a significant increase in sunspot numbers, it can inform other physical consequences that may be caused. The data used was the data of monthly sunspot numbers obtained from SILSO website. The data division and parameters used were based on the results of the trials resulted in the smallest MAPE value. The smallest MAPE value obtained from the prediction was 7.171% with 70% training data, 30% testing data, 150 hidden layer, 32 batch size, 100 learning rate drop.

Item Type: Article
Additional Information:
Arfianti, Unix Izyah
Novitasari, Dian Candra Rini
Widodo, Nanang
Hafiyusholeh, Moh.
Utami, Wika Dianita
Uncontrolled Keywords: Prediction; sunspot numbers; time series; GRU; LSTM
Subjects: 01 MATHEMATICAL SCIENCES > 0101 Pure Mathematics > 010101 Algebra and Number Theory
01 MATHEMATICAL SCIENCES > 0105 Mathematical Physics > 010501 Algebraic Structures in Mathematical Physics
Divisions: Fakultas Sains dan Teknologi > Prodi Matematika
Depositing User: Samidah Nurmayuni
Date Deposited: 14 Jun 2022 02:44
Last Modified: 14 Jun 2022 02:44

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