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.

针对厄尔尼诺/拉尼娜现象的监测预报，本文提出了一种基于长短期记忆神经网络的海面温度预测方法，用于NINO综合区海面平均温度。该方法以NINO综合区平均海表温度的月异常海表温度序列作为长短期记忆神经网络的输入，建立预测模型。预测未来1～3个月NINO综合区海面平均温度。结果表明，该方法能较好地预测NINO综合区海面平均温度，对厄尔尼诺/拉尼娜现象的监测预报具有参考价值。提供了一种新的方法。