Comparison of ARIMA model, DNN model and LSTM model in predicting disease burden of occupational pneumoconiosis in Tianjin, China

Comparison of ARIMA model, DNN model and LSTM model in predicting disease burden of occupational pneumoconiosis in Tianjin, China

Abstract Background This study aims to explore appropriate model for predicting the disease burden of pneumoconiosis in Tianjin by comparing the prediction effects of Autoregressive Integrated Moving Average (ARIMA) model, Deep Neural Networks (DNN) model and multivariate Long Short-Term Memory Neur...

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Bibliographic Details
Main Authors: He-Ren Lou, Xin Wang, Ya Gao, Qiang Zeng
Format: Article
Language:English
Published: BMC 2022-11-01
Series:BMC Public Health
Subjects:
Pneumoconiosis
DALY
ARIMA
DNN
LSTM
Online Access:https://doi.org/10.1186/s12889-022-14642-3

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