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- W4324349625 abstract "Abstract In this paper, an optimized long short-term memory model is proposed to deal with the smoothed monthly F 10.7 and nonsmoothed monthly sunspot area (SSA) data, aiming to forecast the peak amplitude of both solar activities and the occurring time for Solar Cycle 25 (SC-25), as well as to obtain the maximum amplitude of sunspot number (SSN) and the reaching time according to the relationships between them. The “reforecast” process in the model uses the latest forecast results obtained from the previous forecast as the input for the next forecasting calculation. The forecasting errors between the forecast and observed peak amplitude of F 10.7 for SC-23 and SC-24 are 2.87% and 1.09%, respectively. The results of this evaluation indicator of SSA for SC-21 to SC-24 were 8.85%, 4.49%, 2.88%, and 4.57%, respectively, and the errors for the occurring time were all within 6 months. The forecast peak amplitude of F 10.7 and SSA for SC-25 is 156.3 and 2562.5 respectively, and the maximum values of SSN are calculated as 147.9 and 213 based on F 10.7 and SSA respectively, which implies that SC-25 will be stronger than SC-24, and that SC-25 will reach its peak at the beginning of 2025." @default.
- W4324349625 created "2023-03-16" @default.
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- W4324349625 date "2023-03-15" @default.
- W4324349625 modified "2023-10-18" @default.
- W4324349625 title "Forecasting Solar Cycle 25 Using an Optimized Long Short-term Memory Mode Based on F10.7 and Sunspot Area Data" @default.
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- W4324349625 doi "https://doi.org/10.3847/1538-4365/acb650" @default.
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