Hybrid Bat-BP: A New Intelligent Tool for Diagnosing Noise-Induced Hearing Loss (NIHL) in Malaysian Industrial Workers

Abstract:

Noise-Induced Hearing Loss (NIHL) has become a major health threat to the Malaysian industrial workers in the recent era due to exposure to high frequency noise produced by the heavy machines. Recently, many studies have been conducted to diagnose the NIHL in industrial workers but unfortunately they neglected some factors that can play a major role in speeding-up NIHL. In this paper, a new Hybrid Bat-BP algorithm which is based on the trio combination of BAT based metaheuristic optimization, back-propagation neural network, and fuzzy logic is proposed to diagnose NIHL in Malaysian industrial workers. The proposed Hybrid Bat-BP will use heat, body mass index (BMI), diabetes, and smoking along with the century old audiometric variables (i.e. age, frequency, and duration of exposure) to better predict NIHL in Malaysian workers. The results obtained through Hybrid Bat-BP will be able to help us identify and reduce the NIHL rate in the workers with high accuracy.

• Periodical: Applied Mechanics and Materials (Volumes 465-466)
• Pages: 652-656
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.465-466.652
• Online since: December 2013
• Authors: Nazri Mohd Nawi, Muhammad Zubair Rehman*, Mohd Imran Ghazali, Musli Nizam Bin Yahya, Abdullah Khan
• Keywords: Back-Propagation Neural Network, Fuzzy Expert Systems, Fuzzy Logic, Hearing Impairment, Hybrid Bat-BP Algorithm, Noise, Noise-Induced Hearing Loss (NIHL)

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