Prediction of classroom reverberation time using neural network

Zainudin, Fathin Liyana and Mahamad, Abd Kadir and Saon, Sharifah and Yahya, Musli Nizam (2018) Prediction of classroom reverberation time using neural network. Journal of Physics: Conference Series, 995. pp. 1-8. ISSN 1742-6588

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In this paper, an alternative method for predicting the reverberation time (RT) using neural network (NN) for classroom was designed and explored. Classroom models were created using Google SketchUp software. The NN applied training dataset from the classroom models with RT values that were computed from ODEON 12.10 software. The NN was conducted separately for 500Hz, 1000Hz, and 2000Hz as absorption coefficient that is one of the prominent input variable is frequency dependent. Mean squared error (MSE) and regression (R) values were obtained to examine the NN efficiency. Overall, the NN shows a good result with MSE < 0.005 and R > 0.9. The NN also managed to achieve a percentage of accuracy of 92.53% for 500Hz, 93.66% for 1000Hz, and 93.18% for 2000Hz and thus displays a good and efficient performance. Nevertheless, the optimum RT value is range between 0.75 – 0.9 seconds.

Item Type: Article
Uncontrolled Keywords: NIL
Subjects: T Technology > T Technology (General)
T Technology > TK Electrical engineering. Electronics Nuclear engineering
Q Science > QC Physics > QC501-766 Electricity and magnetism > QC501-(721) Electricity
Divisions: Faculty of Electrical and Electronic Engineering > Department of Electronic Enngineering
Depositing User: UiTM Student Praktikal
Date Deposited: 17 Jan 2022 01:07
Last Modified: 17 Jan 2022 01:07

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