Multidimensional Time Series Prediction Based on Quaternion Long Short-term Memory Network
Multidimensional time series data exists in real life,including property prices,road traffic flow,CO2 concentra-tions in different regions,and so on.Cyclic neural network(RNN)is a model for effectively processing time series data.Its variant long short-term memory network(LSTM)effectively solves the problem that the reverse propagation path of RNN is too long,which is easy to cause gradient explosion or disappearance.This paper uses quaternions instead of real numbers for network parameter propagation,capturing the internal relationships between multidimensional time series features through the dependence of the internal structure of quaternions,so that the inherent structural information in multidimensional time series features is well preserved.
万方数据
维普
