contributor author | Dan Tian | |
contributor author | Hao Liu | |
contributor author | Shu Chen | |
contributor author | Mingchao Li | |
contributor author | Chengzhao Liu | |
date accessioned | 2022-08-18T12:11:27Z | |
date available | 2022-08-18T12:11:27Z | |
date issued | 2022/07/12 | |
identifier other | %28ASCE%29CO.1943-7862.0002366.pdf | |
identifier uri | http://yetl.yabesh.ir/yetl1/handle/yetl/4286168 | |
description abstract | Many human errors occur in hydraulic engineering construction, and these errors may lead to huge financial losses. A systematic and comprehensive accident analysis is required to reduce the probability of human error. Human error analysis is a lengthy and challenging process because the tendency is for accident data to be presented in text format. In addition, construction human error management requires an intelligent and efficient analysis system to ensure the timeliness of accident prevention and control. Thus, this study proposes a human error intelligent analysis system on the basis of text mining to automatically extract text knowledge and reveal the accident evolution process. Using hydraulic engineering construction text, a topic feature extraction model is built to extract words and improve the human factors analysis and classification system (HFACS) model. Then, a human error causation network that integrates text topic features, the improved HFACS model, and Bayesian theory is developed to intelligently identify human factors and quantify the human error evolution process. The analysis system proposed in this paper provides an effective way to mine and apply the experience-based knowledge available in hydraulic engineering construction text for the intelligent analysis and prediction of human error, thus improving the efficiency of human error management. | |
publisher | ASCE | |
title | Human Error Analysis for Hydraulic Engineering: Comprehensive System to Reveal Accident Evolution Process with Text Knowledge | |
type | Journal Article | |
journal volume | 148 | |
journal issue | 9 | |
journal title | Journal of Construction Engineering and Management | |
identifier doi | 10.1061/(ASCE)CO.1943-7862.0002366 | |
journal fristpage | 04022093 | |
journal lastpage | 04022093-13 | |
page | 13 | |
tree | Journal of Construction Engineering and Management:;2022:;Volume ( 148 ):;issue: 009 | |
contenttype | Fulltext | |