Modeling important factors on occupational accident severity factor in the construction industry using a combination of artificial neural network and genetic algorithm.
BACKGROUND: Many occupational accidents annually occur worldwide. The construction industry injury is greater than the average injury to other industries. The severity of occupational accidents and the resulting injuries in these industries is very high and severe and several factors are involved in...
| Publicado en: | Work Vol. 73; no. 1; pp. 189 - 203 |
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| Autores principales: | , , , , , |
| Formato: | equations & formulas research tables/charts Journal Article |
| Publicado: |
Sage Publications Inc.
2022
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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=159469090&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 159469090 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 10519815 3RC jtl: Work issn: 10519815 maglogo: N pubinfo: dt: 2022 vid: 73 iid: 1 pid: 344 pub: Sage Publications Inc. place: Thousand Oaks, California artinfo: ui: 159469090 158107634 159469090 159469090 10.3233/WOR-205271 159469090 ppf: 189 ppct: 14 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Modeling important factors on occupational accident severity factor in the construction industry using a combination of artificial neural network and genetic algorithm. aug: au: Mohammadian, Farough Sadeghi, Mehran Hanifi, Saber Moradi Noorizadeh, Najaf Abedi, Kamaladdin Fazli, Zohreh affil: Department of Occupational Health Engineering, Environmental Health Research Center, Research Institute for Health Development, Kurdistan University of Medical Sciences, Sanandaj, Iran sug: subj: Accidents, Occupational Epidemiology Severity of Injury Construction Industry Neural Networks (Computer) Utilization Genetic Algorithms Utilization Prediction Models Human Iran Census Program Implementation Descriptive Statistics Cross Sectional Studies Descriptive Research Data Mining Risk Assessment Work Environment Occupational Safety ROC Curve ab: BACKGROUND: Many occupational accidents annually occur worldwide. The construction industry injury is greater than the average injury to other industries. The severity of occupational accidents and the resulting injuries in these industries is very high and severe and several factors are involved in their occurrence. OBJECTIVE: Modeling important factors on occupational accident severity factor in the construction industry using a combination of artificial neural network and genetic algorithm. METHODS: In this study, occupational accidents were analyzed and modeled during five years at construction sites of 5 major projects affiliated with a gas turbine manufacturing company based on census sampling. 712 accidents with all the studied variables were selected for the study. The process was implemented in MATLAB software version 2018a using combined artificial neural network and genetic algorithm. Additional information was also collected through checklists and interviews. RESULTS: Mean and standard deviation of accident severity rate (ASR) were obtained 283.08±102.55 days. The structure of the model is 21, 42, 42, 2, indicating that the model consists of 21 inputs (selected feature), 42 neurons in the first hidden layer, 42 neurons in the second hidden layer, and 2 output neurons. The two methods of genetic algorithm and artificial neural network showed that the severity rate of accidents and occupational injuries in this industry follows a systemic flow and has different causes. CONCLUSION: The model created based on the selected parameters is able to predict the accident occurrence based on working conditions, which can help decision makers in developing preventive strategies. pubtype: Academic Journal doctype: equations & formulas research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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