Ionized layer TEC content prediction method based on artificial intelligence technology

The invention discloses an ionosphere TEC content prediction method based on an artificial intelligence technology, and the method comprises the steps: S1, resolving and processing historical TEC data and auxiliary input data, S2, building an extended coding and decoding long-short-term memory extension (ED-LSTME) neural network, S3, optimizing the parameters of the extended coding and decoding long-short-term memory extension (ED-LSTME) neural network, s4, evaluating the prediction effect of the extended coding and decoding long-short term memory extension (ED-LSTME) neural network; compared with the prior art, the method has the beneficial effects that the extended coding and decoding long-short-term memory extension (ED-LSTME) neural network model is established, and historical data and auxiliary data are utilized. According to application efficiency evaluation feedback, model parameters are adjusted, the model is optimized, and Chinese regional ionized layer TEC prediction can be carried out. 本发明公开了一种基于人工