Prediction of Health-Related Leave Days among Workers in the Energy Sector by Means of Genetic Algorithms

Prediction of Health-Related Leave Days among Workers in the Energy Sector by Means of Genetic Algorithms

In this research, a model is proposed for predicting the number of days absent from work due to sick or health-related leave among workers in the industry sector, according to ergonomic, social and work-related factors. It employs selected microdata from the Sixth European Working Conditions Survey...

Full description

Bibliographic Details
Main Authors: Aroa González Fuentes, Nélida M. Busto Serrano, Fernando Sánchez Lasheras, Gregorio Fidalgo Valverde, Ana Suárez Sánchez
Format: Article
Language:English
Published: MDPI AG 2020-05-01
Series:Energies
Subjects:
sick leave
absenteeism
energy sector
genetic algorithms (GA)
multivariate adaptive regression splines (MARS)
Online Access:https://www.mdpi.com/1996-1073/13/10/2475

Internet

https://www.mdpi.com/1996-1073/13/10/2475

Similar Items