A Neuro-Fuzzy Risk Prediction Methodology for Falling From Scaffold

A Neuro-Fuzzy Risk Prediction Methodology for Falling From Scaffold Publisher

Jahangiri M¹ ; Solukloei HRJ² ; Kamalinia M³

Show Affiliations

1. Research Center for Health Science, Department of Occupational Health, School of Health, Shiraz University of Medical Sciences, Shiraz, Iran
2. Department of Occupational Health Engineering, School of Health, Tehran University of Medical Science, Tehran, Iran
3. Department of Occupational Health Engineering, School of Health, Shiraz University of Medical Science, Shiraz, Iran

Source: Safety Science Published:2019

Abstract

Fall from height is one of the most significant safety issues in the construction industry, due to the high number of fatal injuries. Scaffolds are a leading cause and have one of the highest injury rates. Therefore, it is crucial to introduce preventive measures and strategies. This study introduces a hybrid approach that merges an Adaptive Neural Network-based Fuzzy Inference System (ANFIS) and a safety inspection checklist to identify risk factors and predict the risk of falling from scaffold on construction sites. Our findings indicate that platform, joints, ladders, personal protective equipment and guardrails are the most important factors. The approach can identify and assess key conditions and situations that have the greatest impact on fall risk. The hybrid ANFIS–checklist model is found to outperform the regression method in predicting fall risk. Experts can use also this approach in other safety areas to identify and predict workplace risk. © 2019 Elsevier Ltd

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Style	Citing Format
MLA	Jahangiri M, Solukloei HRJ, Kamalinia M. "A Neuro-Fuzzy Risk Prediction Methodology for Falling From Scaffold." Safety Science, vol. 117, no. , 2019, pp. 88-99.
APA	Jahangiri M, Solukloei HRJ, Kamalinia M (2019). A Neuro-Fuzzy Risk Prediction Methodology for Falling From Scaffold. Safety Science, 117(), 88-99.
Chicago	Jahangiri M, Solukloei HRJ, Kamalinia M. "A Neuro-Fuzzy Risk Prediction Methodology for Falling From Scaffold." Safety Science 117, no. (2019): 88-99.
Harvard	Jahangiri M, Solukloei HRJ, Kamalinia M (2019) 'A Neuro-Fuzzy Risk Prediction Methodology for Falling From Scaffold', Safety Science, 117(), pp. 88-99.
Vancouver	Jahangiri M, Solukloei HRJ, Kamalinia M. A Neuro-Fuzzy Risk Prediction Methodology for Falling From Scaffold. Safety Science. 2019;117():88-99.
BibTex	@article{ author = {Jahangiri M and Solukloei HRJ and Kamalinia M}, title = {A Neuro-Fuzzy Risk Prediction Methodology for Falling From Scaffold}, journal = {Safety Science}, volume = {117}, number = {}, pages = {88-99}, year = {2019} }
RIS	TY - JOUR AU - Jahangiri M AU - Solukloei HRJ AU - Kamalinia M TI - A Neuro-Fuzzy Risk Prediction Methodology for Falling From Scaffold JO - Safety Science VL - 117 IS - SP - 88 EP - 99 PY - 2019 ER -

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