Combining Deep Neural Networks and Classical Time Series Regression Models for Forecasting Patient Flows in Hong Kong

Combining Deep Neural Networks and Classical Time Series Regression Models for Forecasting Patient Flows in Hong Kong

Deep Neural Networks (DNNs) has been dominating recent data mining related tasks with better performances. This article proposes a hybrid approach that exploits the unique predictive power of DNN and classical time series regression models, including Generalized Linear Model (GLM), Seasonal AutoRegr...

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Bibliographic Details
Main Authors: Shancheng Jiang, Ran Xiao, Long Wang, Xiong Luo, Chao Huang, Jenq-Haur Wang, Kwai-Sang Chin, Ximing Nie
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Data mining
deep neural networks
hybrid approach
time series regression
data mining
Online Access:https://ieeexplore.ieee.org/document/8808897/

Internet

https://ieeexplore.ieee.org/document/8808897/

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