Staff View: Predicting and modeling the effects of turbines noise on operator’s mental task performance in AL-DORA power plant

Predicting and modeling the effects of turbines noise on operator’s mental task performance in AL-DORA power plant

Noise has become one of the most critical environmental challenges. As one of noise kinds, the discomfort level of environmental noise can affect both personal quality of life and hearing sensitivity. An example is workplace noise pollution, which affects employees’ regular functioning and profoundl...

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Main Authors:	Mosa, Ali I., Al-Sadawi, Laith A., Attia, Osam H., Adam, Nor Mariah
Format:	Article
Language:	English
Published:	Scientific Route 2024
Online Access:	http://psasir.upm.edu.my/id/eprint/114398/1/114398.pdf http://psasir.upm.edu.my/id/eprint/114398/ https://journal.eu-jr.eu/engineering/article/view/3390
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spelling	my.upm.eprints.1143982025-01-15T01:39:42Z http://psasir.upm.edu.my/id/eprint/114398/ Predicting and modeling the effects of turbines noise on operator’s mental task performance in AL-DORA power plant Mosa, Ali I. Al-Sadawi, Laith A. Attia, Osam H. Adam, Nor Mariah Noise has become one of the most critical environmental challenges. As one of noise kinds, the discomfort level of environmental noise can affect both personal quality of life and hearing sensitivity. An example is workplace noise pollution, which affects employees’ regular functioning and profoundly impacts their mental, auditory health, and psychological well-being. In order to tackle these issues, the need for adaptive intelligent systems has significantly grown. This study aims to evolve a neuro-fuzzy model for predicting the effects of noise pollution on employee’s work efficiency as a function of noise level and exposure time at Al-DORA Power Plant in Baghdad city. Participants’ responses were used to develop a neural-fuzzy logic model based on artificial neural networks (ANN) and fuzzy inference systems (FIS). The model is performed using the fuzzy logic toolbox inherited from the MATLAB software. The measurements were carried out for duration of nine weeks, three times a day during summer, and the extensive noise level was up to 110 dB. Results in the trapezoidal-shaped membership form showed a discernible pattern or trend in the fluctuation of membership degree in relation to noise levels. The same trend could be seen for the exposure time. Furthermore, the results showed that the efficiency of the workers depends on the noise level and exposure duration. It has been confirmed that a medium noise level can influence workers’ performance over a medium exposure time to a certain degree. Moreover, low noise levels can still affect the performance of workers who are exposed to noise for long durations. With this clear relationship between noise levels, exposure time, and mental work efficiency, organizations can implement certain strategies to optimize their acoustic environments. Scientific Route 2024 Article PeerReviewed text en cc_by_4 http://psasir.upm.edu.my/id/eprint/114398/1/114398.pdf Mosa, Ali I. and Al-Sadawi, Laith A. and Attia, Osam H. and Adam, Nor Mariah (2024) Predicting and modeling the effects of turbines noise on operator’s mental task performance in AL-DORA power plant. EUREKA, Physics and Engineering (5). pp. 173-182. ISSN 2461-4254; eISSN: 2461-4262 https://journal.eu-jr.eu/engineering/article/view/3390 10.21303/2461-4262.2024.003390
institution	Universiti Putra Malaysia
building	UPM Library
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	Universiti Putra Malaysia
content_source	UPM Institutional Repository
url_provider	http://psasir.upm.edu.my/
language	English
description	Noise has become one of the most critical environmental challenges. As one of noise kinds, the discomfort level of environmental noise can affect both personal quality of life and hearing sensitivity. An example is workplace noise pollution, which affects employees’ regular functioning and profoundly impacts their mental, auditory health, and psychological well-being. In order to tackle these issues, the need for adaptive intelligent systems has significantly grown. This study aims to evolve a neuro-fuzzy model for predicting the effects of noise pollution on employee’s work efficiency as a function of noise level and exposure time at Al-DORA Power Plant in Baghdad city. Participants’ responses were used to develop a neural-fuzzy logic model based on artificial neural networks (ANN) and fuzzy inference systems (FIS). The model is performed using the fuzzy logic toolbox inherited from the MATLAB software. The measurements were carried out for duration of nine weeks, three times a day during summer, and the extensive noise level was up to 110 dB. Results in the trapezoidal-shaped membership form showed a discernible pattern or trend in the fluctuation of membership degree in relation to noise levels. The same trend could be seen for the exposure time. Furthermore, the results showed that the efficiency of the workers depends on the noise level and exposure duration. It has been confirmed that a medium noise level can influence workers’ performance over a medium exposure time to a certain degree. Moreover, low noise levels can still affect the performance of workers who are exposed to noise for long durations. With this clear relationship between noise levels, exposure time, and mental work efficiency, organizations can implement certain strategies to optimize their acoustic environments.
format	Article
author	Mosa, Ali I. Al-Sadawi, Laith A. Attia, Osam H. Adam, Nor Mariah
spellingShingle	Mosa, Ali I. Al-Sadawi, Laith A. Attia, Osam H. Adam, Nor Mariah Predicting and modeling the effects of turbines noise on operator’s mental task performance in AL-DORA power plant
author_facet	Mosa, Ali I. Al-Sadawi, Laith A. Attia, Osam H. Adam, Nor Mariah
author_sort	Mosa, Ali I.
title	Predicting and modeling the effects of turbines noise on operator’s mental task performance in AL-DORA power plant
title_short	Predicting and modeling the effects of turbines noise on operator’s mental task performance in AL-DORA power plant
title_full	Predicting and modeling the effects of turbines noise on operator’s mental task performance in AL-DORA power plant
title_fullStr	Predicting and modeling the effects of turbines noise on operator’s mental task performance in AL-DORA power plant
title_full_unstemmed	Predicting and modeling the effects of turbines noise on operator’s mental task performance in AL-DORA power plant
title_sort	predicting and modeling the effects of turbines noise on operator’s mental task performance in al-dora power plant
publisher	Scientific Route
publishDate	2024
url	http://psasir.upm.edu.my/id/eprint/114398/1/114398.pdf http://psasir.upm.edu.my/id/eprint/114398/ https://journal.eu-jr.eu/engineering/article/view/3390
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score	13.244109

Predicting and modeling the effects of turbines noise on operator’s mental task performance in AL-DORA power plant

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