Development of a Noise Prediction Model Based on Advanced Fuzzy Approaches in Typical Industrial Workrooms.
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...
| Publicado en: | Journal of Research in Health Sciences Vol. 14; no. 2; pp. 157 - 163 |
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| Autores principales: | , , , , |
| Formato: | research tables/charts Journal Article |
| Publicado: |
Hamadan University of Medical Sciences, School of Public Health
2014
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=96223476&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 96223476 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 22287795 903Q jtl: Journal of Research in Health Sciences issn: 22287795 maglogo: N pubinfo: dt: 2014 vid: 14 iid: 2 pid: 54266 pub: Hamadan University of Medical Sciences, School of Public Health artinfo: ui: 96223476 96223476 103951641 96223476 ppf: 157 ppct: 6 formats: fmt: @attributes: type: P tig: atl: Development of a Noise Prediction Model Based on Advanced Fuzzy Approaches in Typical Industrial Workrooms. aug: au: Aliabadi, Mohsen Golmohammadi, Rostam Khotanlou, Hassan Mansoorizadeh, Muharram Salarpour, Amir affil: Department of Occupational Hygiene, Faculty of Public Health and Research Center for Health Sciences, Hamadan University of Medical Sciences, Hamadan, Iran sug: subj: Noise Analysis Industry Evaluation Funding Source Human Iran Descriptive Statistics Multiple Regression Occupational Safety ab: 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. pubtype: Academic Journal doctype: research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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