Neural network forecasting method for navigation satellite clock error data

The invention provides a neural network forecasting method for navigation satellite clock error data, and the method comprises the steps: building a short-term clock error forecasting model which combines an SSA (Sparrow Search Algorithm) with a BiLSTM (Bidirectional Long Short-Term Memory Neural Ne...

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Bibliographische Detailangaben
Hauptverfasser:	ZHANG SIYING, PAN XIONG, HUANG WEIKAI, ZHAO WANZHUO, ZHONG SAISHANG, JIN LIHONG
Format:	Patent
Sprache:	chi ; eng
Schlagworte:	ANALOGOUS ARRANGEMENTS USING OTHER WAVES CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION ORRERADIATION OF RADIO WAVES MEASURING PHYSICS RADIO DIRECTION-FINDING RADIO NAVIGATION TESTING
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Beschreibung
Zusammenfassung:	The invention provides a neural network forecasting method for navigation satellite clock error data, and the method comprises the steps: building a short-term clock error forecasting model which combines an SSA (Sparrow Search Algorithm) with a BiLSTM (Bidirectional Long Short-Term Memory Neural Network), carrying out the reverse extension of a neural network layer of the LSTM, building a BiLSTM, carrying out the reverse extension of the neural network layer of the BiLSTM, carrying out the reverse extension of the neural network layer of the BiLSTM, carrying out the reverse extension of the neural network layer of the BiLSTM, carrying out the reverse extension of the neural network layer of the BiLSTM, carrying out the reverse extension of the neural network layer of the BiLSTM, and carrying out the prediction of the clock error data of the navigation satellite. The SSA is combined to effectively solve the problem that neural network hyper-parameters obtained through human experience adjustment in the LSTM c