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Sea surface temperature prediction model based on long and short-term memory neural network

Published under licence by IOP Publishing Ltd
, , Citation Xiaojing Li 2021 IOP Conf. Ser.: Earth Environ. Sci. 658 012040 DOI 10.1088/1755-1315/658/1/012040

1755-1315/658/1/012040

Abstract

In response to the monitoring and forecasting of El Nino/La Nina phenomenon, This paper proposes a sea surface temperature prediction method based on long and short-term memory neural network for the average sea surface temperature in the NINO comprehensive area. This method uses the monthly anomaly sea surface temperature sequence for the mean sea surface temperature in the NINO Comprehensive area as the input of the long- and short-term memory neural network to establish a forecast model. The average sea surface temperature of the NINO comprehensive area is forecasted for the next 1 to 3 months. The results show that the method can better predict the average sea surface temperature of the NINO comprehensive area, which is useful for the monitoring and forecasting of El Nino/La Nina phenomenon. Provides a new approach.

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