River estuary deepwater channel back-silting amount prediction method based on big data

The invention provides a method/model for predicting the back-silting amount of a river estuary deepwater channel based on big data (actually measured data), the back-silting amount of a channel (monthly) for river estuary deepwater channel dredging can be predicted quickly with high precision, and an important reference index is provided for making a dredging construction capacity arrangement plan. The prediction big data of the river estuary deepwater channel back-silting amount comprises flow, water temperature, tide level, tidal range, wave energy and channel unit water depth. According tothe method/model for predicting the back-silting amount of the deepwater channel, deep learning can be continuously carried out along with accumulation of big data, and the method/model has the characteristic of self-perfection, so that the prediction precision is further improved. The method has important guiding significance in reducing waste of the construction capacity, guaranteeing the navigation guarantee rate of t