Research on tidal missing data imputing with long and short term memory neural network
Tidal data reflects changes in coastal sea level,and plays a very important role in various fields.The lack of tidal data brings inconvenience to the use of tide level data.Based on the tidal data of the Chongwu and Jinjiang ocean stations in 2017,this paper proposed a method of filling missing data based on the LSTM model(long short-term memory neural network model).Compared with tradition-al interpolation methods such as linear interpolation and spline interpolation,the LSTM method had stable performance,high accuracy and easy implementation.Especially when the lack of measurement time was long,the LSTM method was obviously better than the traditional interpolation method.At the same time,this method was also suitable for filling other missing data including water temperature.
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