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Mathematical Problems in Engineering
Volume 2014, Article ID 756326, 10 pages
http://dx.doi.org/10.1155/2014/756326
Research Article

An Artificial Neural Networks Approach to Estimate Occupational Accident: A National Perspective for Turkey

Kırıkkale Vocational School, Kırıkkale University, 71451 Kırıkkale, Turkey

Received 30 October 2014; Accepted 1 December 2014; Published 28 December 2014

Academic Editor: Leonid Shaikhet

Copyright © 2014 Hüseyin Ceylan. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Occupational accident estimation models were developed by using artificial neural networks (ANNs) for Turkey. Using these models the number of occupational accidents and death and permanent incapacity numbers resulting from occupational accidents were estimated for Turkey until the year of 2025 by the three different scenarios. In the development of the models, insured workers, workplace, occupational accident, death, and permanent incapacity values were used as model parameters with data between 1970 and 2012. 2-5-1 neural network architecture was selected as the best network architecture. Sigmoid was used in hidden layers and linear function was used at output layer. The feed forward back propagation algorithm was used to train the network. In order to obtain a useful model, the network was trained between 1970 and 1999 to estimate the values of 2000 to 2012. The result was compared with the real values and it was seen that it is applicable for this aim. The performances of all developed models were evaluated using mean absolute percent errors (MAPE), mean absolute errors (MAE), and root mean square errors (RMSE).