Sunspot Time Series Forecasting using Deep
Learning
Dublin Core
Title
Sunspot Time Series Forecasting using Deep
Learning
Learning
Subject
order to forecast solar cycle 25
Description
Abstract:In order to forecast solar cycle 25, sunspot numbers(SSN) from
1700 2018 was used as a time series to predict the next eleven years.
deep long short-term memory(LSTM) was exploited to do the forecast, rst
the dataset was split into training set(80%) and (20%) for the test set, the
achieved accuracy led us to forecast the next eleven years. The result shows
that the cycle will be from 2019 2029 with peak at 2024.
1700 2018 was used as a time series to predict the next eleven years.
deep long short-term memory(LSTM) was exploited to do the forecast, rst
the dataset was split into training set(80%) and (20%) for the test set, the
achieved accuracy led us to forecast the next eleven years. The result shows
that the cycle will be from 2019 2029 with peak at 2024.
Creator
Mahmoud Elgamal
Source
www.ijcit.com
Date
March 2020
Contributor
peri irawan
Format
pdf
Language
english
Type
text
Files
Collection
Citation
Mahmoud Elgamal, “Sunspot Time Series Forecasting using Deep
Learning,” Repository Horizon University Indonesia, accessed May 23, 2025, https://repository.horizon.ac.id/items/show/8892.
Learning,” Repository Horizon University Indonesia, accessed May 23, 2025, https://repository.horizon.ac.id/items/show/8892.