Development of a Noise Prediction Model Based on Advanced Fuzzy Approaches in Typical Industrial Workrooms
Author(s):
Abstract:
Background
Noise prediction is considered to be the best method for evaluating cost-preventative noise controls in industrial workrooms. One of the most important issues is the development of accurate models for analysis of the complex relationships among acoustic features affecting noise level in workrooms. In this study، advanced fuzzy approaches were employed to develop relatively accurate models for predicting noise in noisy industrial workrooms. Methods
The data were collected from 60 industrial embroidery workrooms in the Khorasan Province، East of Iran. The main acoustic and embroidery process features that influence the noise were used to develop prediction models using MATLAB software. Multiple regression technique was also employed and its results were compared with those of fuzzy approaches. Results
Prediction errors of all prediction models based on fuzzy approaches were within the acceptable level (lower than one dB). However، Neuro-fuzzy model (RMSE=0. 53dB and R2=0. 88) could slightly improve the accuracy of noise prediction compared with generate fuzzy model. Moreover، fuzzy approaches provided more accurate predictions than did regression technique. Conclusions
The developed models based on fuzzy approaches as useful prediction tools give professionals the opportunity to have an optimum decision about the effectiveness of acoustic treatment scenarios in embroidery workrooms.Keywords:
Language:
English
Published:
Journal of Research in Health Sciences, Volume:14 Issue: 2, Spring 2014
Pages:
157 to 162
https://www.magiran.com/p1261206
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