Within this regard, this paper selects Poyang Lake as the investigate object, adopts the transformer neural network system to establish the prediction design of day-to-day scale of water volume of Poyang Lake, and explores its opportunity to predict the water level improve process of Poyang Lake. We Review the simulation benefits of transformer product with other deep Discovering networks for example LSTM, and distinguish the influences of inflows in the “5 river” and Yangtze River discharges about the lake water variations. We current an analysis the results of hyper-parameters and forecasting lead time on design accuracy. The contribution factors of the examine are as follows: (one) This is the to start with examine to use deep Understanding product coupling Along with the self-consideration system on lake water degree prediction.
Water-resistant
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Tragic Demise of supporting actress Yang Sora following sexual assault by filming staff members and police negligence
Precisely, we initially input the sequence knowledge X into the transformer, then add the positional embeddings on the enter attributes to get the first layer input representations H t 0