A Comparative Study on the Prediction of Occupational Diseases in China with Hybrid Algorithm Combing Models
Joint Authors
Lu, Yaoqin
Yan, Huan
Zhang, Lijiang
Liu, Jiwen
Source
Computational and Mathematical Methods in Medicine
Issue
Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2019-09-29
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
Occupational disease is a huge problem in China, and many workers are under risk.
Accurate forecasting of occupational disease incidence can provide critical information for prevention and control.
Therefore, in this study, five hybrid algorithm combing models were assessed on their effectiveness and applicability to predict the incidence of occupational diseases in China.
The five hybrid algorithm combing models are the combination of five grey models (EGM, ODGM, EDGM, DGM, and Verhulst) and five state-of-art machine learning models (KNN, SVM, RF, GBM, and ANN).
The quality of the models were assessed based on the accuracy of model prediction as well as minimizing mean absolute percentage error (MAPE) and root-mean-squared error (RMSE).
Our results showed that the GM-ANN model provided the most precise prediction among all the models with lowest mean absolute percentage error (MAPE) of 3.49% and root-mean-squared error (RMSE) of 1076.60.
Therefore, the GM-ANN model can be used for precise prediction of occupational diseases in China, which may provide valuable information for the prevention and control of occupational diseases in the future.
American Psychological Association (APA)
Lu, Yaoqin& Yan, Huan& Zhang, Lijiang& Liu, Jiwen. 2019. A Comparative Study on the Prediction of Occupational Diseases in China with Hybrid Algorithm Combing Models. Computational and Mathematical Methods in Medicine،Vol. 2019, no. 2019, pp.1-10.
https://search.emarefa.net/detail/BIM-1130728
Modern Language Association (MLA)
Lu, Yaoqin…[et al.]. A Comparative Study on the Prediction of Occupational Diseases in China with Hybrid Algorithm Combing Models. Computational and Mathematical Methods in Medicine No. 2019 (2019), pp.1-10.
https://search.emarefa.net/detail/BIM-1130728
American Medical Association (AMA)
Lu, Yaoqin& Yan, Huan& Zhang, Lijiang& Liu, Jiwen. A Comparative Study on the Prediction of Occupational Diseases in China with Hybrid Algorithm Combing Models. Computational and Mathematical Methods in Medicine. 2019. Vol. 2019, no. 2019, pp.1-10.
https://search.emarefa.net/detail/BIM-1130728
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1130728