title: Development of a noise prediction model based on advanced fuzzy approaches in typical industrial workrooms.
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.
authors.affiliation: Department of Occupational Hygiene, Faculty of public health and Research Center for Health Sciences, Hamadan University of Medical Sciences, Hamadan, Iran.
authors.forename: Mohsen
authors.initials: M
authors.lastname: Aliabadi
authors.affiliation: Department of Occupational Hygiene, Faculty of public health and Research Center for Health Sciences, Hamadan University of Medical Sciences, Hamadan, Iran. golmohamadi@umsha.ac.ir.
authors.forename: Rostam
authors.initials: R
authors.lastname: Golmohammadi
authors.affiliation: Department of Computer Engineering, Faculty of Engineering, Bu-Ali Sina University, Hamadan ,Iran.
authors.forename: Hassan
authors.initials: H
authors.lastname: Khotanlou
authors.affiliation: Department of Computer Engineering, Faculty of Engineering, Bu-Ali Sina University, Hamadan ,Iran.
authors.forename: Muharram
authors.initials: M
authors.lastname: Mansoorizadeh
authors.affiliation: Department of Computer Engineering, Faculty of Engineering, Bu-Ali Sina University, Hamadan ,Iran.
authors.forename: Amir
authors.initials: A
authors.lastname: Salarpour
mesh_terms: D000162:Acoustics; D017143:Fuzzy Logic; D006801:Humans; D007221:Industry; D007492:Iran; D008962:Models, Theoretical; D009622:Noise; D016273:Occupational Exposure
keywords: Advanced Fuzzy; Industrial Workrooms; Noise; Prediction Model