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

Dynamic fire risk prevention strategy in underground coal gasification processes by means of artificial neural networks

(2023) Alicja Krzemień   Archives of Mining Sciences

Optimal Reconfiguration of Distribution Networks Using Hybrid Heuristic-Genetic Algorithm

(2020) Damir Jakus et al.   Energies

Fire risk prevention in underground coal gasification (UCG) within active mines: Temperature forecast by means of MARS models

(2019) Alicja Krzemień   ENERGY

Sick leave due to musculoskeletal pain: determinants of distinct trajectories over 1 year

(2019) David M. Hallman et al.   INTERNATIONAL ARCHIVES OF OCCUPATIONAL AND ENVIRONMENTAL HEALTH

Prediction of Computer Vision Syndrome in Health Personnel by Means of Genetic Algorithms and Binary Regression Trees

(2019) Eva María Artime Ríos et al.   SENSORS

A General Approach in Optimization of Heat Exchangers by Bio-Inspired Artificial Intelligence Methods

(2019) Jaroslaw Krzywanski   Energies

A psychosocial theory of sick leave put to the test in the European Working Conditions Survey 2010–2015

(2019) Diego Montano   INTERNATIONAL ARCHIVES OF OCCUPATIONAL AND ENVIRONMENTAL HEALTH

Identification of gender differences in the factors influencing shoulders, neck and upper limb MSD by means of multivariate adaptive regression splines (MARS)

(2019) N. Busto Serrano et al.   APPLIED ERGONOMICS

Association between Exposure to Extreme Temperature and Injury at the Workplace

(2019) Junhyeong Lee et al.   International Journal of Environmental Research and Public Health

Genetic algorithm based on support vector machines for computer vision syndrome classification in health personnel

(2018) Eva María Artime Ríos et al.   NEURAL COMPUTING & APPLICATIONS

A hybrid ARIMA–SVM model for the study of the remaining useful life of aircraft engines

(2018) Celestino Ordóñez et al.   JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS

Applying the K-nearest neighbor technique to the classification of workers according to their risk of suffering musculoskeletal disorders

(2016) A. Suárez Sánchez et al.   INTERNATIONAL JOURNAL OF INDUSTRIAL ERGONOMICS

Fatores de risco para absenteísmo com licença médica em trabalhadores da indústria de petróleo

(2014) Nágila Soares Xavier Oenning et al.   REVISTA DE SAUDE PUBLICA

Forecasting the cyanotoxins presence in fresh waters: A new model based on genetic algorithms combined with the MARS technique

(2012) J.R. Alonso Fernández et al.   ECOLOGICAL ENGINEERING

An ANN-Based Smart Tomographic Reconstructor in a Dynamic Environment

(2012) Francisco J. de Cos Juez et al.   SENSORS

Prediction of work-related accidents according to working conditions using support vector machines

(2011) A. Suárez Sánchez et al.   APPLIED MATHEMATICS AND COMPUTATION

Study of cyanotoxins presence from experimental cyanobacteria concentrations using a new data mining methodology based on multivariate adaptive regression splines in Trasona reservoir (Northern Spain)

(2011) P.J. Garcia Nieto et al.   JOURNAL OF HAZARDOUS MATERIALS

Applying generalised feedforward neural networks to classifying industrial jobs in terms of risk of low back disorders

(2010) S. Asensio-Cuesta et al.   INTERNATIONAL JOURNAL OF INDUSTRIAL ERGONOMICS

Interrelationships between education, occupational class, income and sickness absence

(2009) K. Piha et al.   EUROPEAN JOURNAL OF PUBLIC HEALTH