Prediction of hearing loss among the noise-exposed workers in a steel factory using artificial intelligence approach
Author:
Publisher
Springer Science and Business Media LLC
Subject
Public Health, Environmental and Occupational Health
Link
http://link.springer.com/content/pdf/10.1007/s00420-014-1004-z.pdf
Reference41 articles.
1. Adera T, Amir C, Anderson L (2004) Time trends analysis of hearing loss: an alternative approach to evaluating hearing loss prevention programs. AIHA J 61:161–165
2. Aliabadi M, Golmohammadi R, Mansoorizadeh M, Khotanlou H, Ohadi A (2013) An empirical technique for predicting noise exposure level in the typical embroidery workrooms using artificial neural networks. Appl Acoust 74:364–374
3. Basheer IA, Hajmeer M (2000) Artificial neural networks: fundamentals, computing, design, and application. J Microbiol Method 43:3–31
4. Black J, Benke G, Smith K, Fritschi L (2004) Artificial neural networks and job-specific modules to assess occupational exposure. Ann Occup Hyg 48:595–600
5. Chang SJ, Chang CK (2009) Prevalence and risk factors of noise-induced hearing loss among liquefied petroleum gas (LPG) cylinder infusion workers in Taiwan. Ind Health 47:603–610
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