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Development of noise induced hearing loss prediction model using Levenberg Marquardt / Siti Fairus Mohd Zain … [et al.]

This research explores the creation of a noise-induced hearing loss (NIHL) prediction model. In the context of occupational health, NIHL is defined as hearing loss that occurs as a result of overexposure to noise hazards at work for a given noise level and time. Despite the high statistical instance...

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Main Authors: Mohd Zain, Siti Fairus, Sulaiman, Ahamad Asari, Yasin, Siti Munira, Zamhuri, Mohammad Idris, Abdullah Hair, Ahmad Fitri, Hussin, Mohamad Fahmi, Ismail, Ismaniza
格式: Article
语言:English
出版: UiTM Press 2023
主题:
Probes (Electronic instruments)
在线阅读:https://ir.uitm.edu.my/id/eprint/76339/1/76339.pdf
https://ir.uitm.edu.my/id/eprint/76339/
https://jeesr.uitm.edu.my/
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spelling my.uitm.ir.763392023-04-13T06:18:47Z https://ir.uitm.edu.my/id/eprint/76339/ Development of noise induced hearing loss prediction model using Levenberg Marquardt / Siti Fairus Mohd Zain … [et al.] jeesr Mohd Zain, Siti Fairus Sulaiman, Ahamad Asari Yasin, Siti Munira Zamhuri, Mohammad Idris Abdullah Hair, Ahmad Fitri Hussin, Mohamad Fahmi Ismail, Ismaniza Probes (Electronic instruments) This research explores the creation of a noise-induced hearing loss (NIHL) prediction model. In the context of occupational health, NIHL is defined as hearing loss that occurs as a result of overexposure to noise hazards at work for a given noise level and time. Despite the high statistical instances that have been recorded over the course of a number of years, there have been very few, if any, efforts made to construct an appropriate prediction model using the combination of linked diagnostic occupational hazards. This study aims to show how an Artificial Neural Network Levenberg-Marquardt algorithm can be used to make a prediction model for NIHL. The goal is to find highly linked risk factors that increase the number of NIHL cases reported in Selangor, Malaysia. The study looked at 355 secondary data points taken from NIHL confirmed cases and given by the Department of Occupational Safety and Health (DOSH). The overall performance of the ANN prediction model was tested at a level of 90.46 percent average. Because of the great accuracy in predicting NIHL, it is inferred that the model may be employed as an intelligent system in the preliminary screening phase. UiTM Press 2023-04 Article PeerReviewed text en https://ir.uitm.edu.my/id/eprint/76339/1/76339.pdf Development of noise induced hearing loss prediction model using Levenberg Marquardt / Siti Fairus Mohd Zain … [et al.]. (2023) Journal of Electrical and Electronic Systems Research (JEESR), 22: 2. pp. 11-18. ISSN 1985-5389 https://jeesr.uitm.edu.my/
institution Universiti Teknologi Mara
building Tun Abdul Razak Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Mara
content_source UiTM Institutional Repository
url_provider http://ir.uitm.edu.my/
language English
topic Probes (Electronic instruments)
spellingShingle Probes (Electronic instruments)
Mohd Zain, Siti Fairus
Sulaiman, Ahamad Asari
Yasin, Siti Munira
Zamhuri, Mohammad Idris
Abdullah Hair, Ahmad Fitri
Hussin, Mohamad Fahmi
Ismail, Ismaniza
Development of noise induced hearing loss prediction model using Levenberg Marquardt / Siti Fairus Mohd Zain … [et al.]
description This research explores the creation of a noise-induced hearing loss (NIHL) prediction model. In the context of occupational health, NIHL is defined as hearing loss that occurs as a result of overexposure to noise hazards at work for a given noise level and time. Despite the high statistical instances that have been recorded over the course of a number of years, there have been very few, if any, efforts made to construct an appropriate prediction model using the combination of linked diagnostic occupational hazards. This study aims to show how an Artificial Neural Network Levenberg-Marquardt algorithm can be used to make a prediction model for NIHL. The goal is to find highly linked risk factors that increase the number of NIHL cases reported in Selangor, Malaysia. The study looked at 355 secondary data points taken from NIHL confirmed cases and given by the Department of Occupational Safety and Health (DOSH). The overall performance of the ANN prediction model was tested at a level of 90.46 percent average. Because of the great accuracy in predicting NIHL, it is inferred that the model may be employed as an intelligent system in the preliminary screening phase.
format Article
author Mohd Zain, Siti Fairus
Sulaiman, Ahamad Asari
Yasin, Siti Munira
Zamhuri, Mohammad Idris
Abdullah Hair, Ahmad Fitri
Hussin, Mohamad Fahmi
Ismail, Ismaniza
author_facet Mohd Zain, Siti Fairus
Sulaiman, Ahamad Asari
Yasin, Siti Munira
Zamhuri, Mohammad Idris
Abdullah Hair, Ahmad Fitri
Hussin, Mohamad Fahmi
Ismail, Ismaniza
author_sort Mohd Zain, Siti Fairus
title Development of noise induced hearing loss prediction model using Levenberg Marquardt / Siti Fairus Mohd Zain … [et al.]
title_short Development of noise induced hearing loss prediction model using Levenberg Marquardt / Siti Fairus Mohd Zain … [et al.]
title_full Development of noise induced hearing loss prediction model using Levenberg Marquardt / Siti Fairus Mohd Zain … [et al.]
title_fullStr Development of noise induced hearing loss prediction model using Levenberg Marquardt / Siti Fairus Mohd Zain … [et al.]
title_full_unstemmed Development of noise induced hearing loss prediction model using Levenberg Marquardt / Siti Fairus Mohd Zain … [et al.]
title_sort development of noise induced hearing loss prediction model using levenberg marquardt / siti fairus mohd zain … [et al.]
publisher UiTM Press
publishDate 2023
url https://ir.uitm.edu.my/id/eprint/76339/1/76339.pdf
https://ir.uitm.edu.my/id/eprint/76339/
https://jeesr.uitm.edu.my/
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score 13.250246

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