2020 2nd International Conference on Machine Learning, Big Data and Business Intelligence (MLBDBI) 2020
DOI: 10.1109/mlbdbi51377.2020.00017
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Analyzing the causation of public accidents caused by urban logistics based on complex network

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Cited by 1 publication
(2 citation statements)
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“…In the domain of three-wheeled motor vehicles, Ijaz et al proposed the use of the Decision Jungle (DJ), Random Forest (RF), and Decision Tree (DT) techniques to investigate the gravity of injuries resulting from traffic accidents, and DJ demonstrated the highest level of accuracy among the three methodologies [18]. Based on complex network theory, Zhao et al established a new model for analyzing the causes of public urban logistics accidents, and analyzed the accidents from a global perspective, identifying the main causes [19]. Guo et al proposed the use of the Extreme Gradient Boost (XGBoost) method to analyze the influencing factors of pedestrian traffic accidents among the elderly and identified driver characteristics, elderly characteristics, and vehicle movement as the most important factors affecting the severity of accidents [20].…”
Section: Related Workmentioning
confidence: 99%
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“…In the domain of three-wheeled motor vehicles, Ijaz et al proposed the use of the Decision Jungle (DJ), Random Forest (RF), and Decision Tree (DT) techniques to investigate the gravity of injuries resulting from traffic accidents, and DJ demonstrated the highest level of accuracy among the three methodologies [18]. Based on complex network theory, Zhao et al established a new model for analyzing the causes of public urban logistics accidents, and analyzed the accidents from a global perspective, identifying the main causes [19]. Guo et al proposed the use of the Extreme Gradient Boost (XGBoost) method to analyze the influencing factors of pedestrian traffic accidents among the elderly and identified driver characteristics, elderly characteristics, and vehicle movement as the most important factors affecting the severity of accidents [20].…”
Section: Related Workmentioning
confidence: 99%
“…The accidents occurred on the right side of the road r 18 The environmental temperature during the accidents was low temperature r 19 The environmental temperature during the accidents was moderate temperature r 20 The environmental temperature during the accidents was high temperature r 21 The environmental humidity during the accidents was dry r 22 The environmental humidity during the accidents was humid r 23 The environmental humidity during the accidents was wetter There was an intersection near the accidents r 35 There was no intersection near the accidents r 36 There was a reducer belt near the accidents r 37 There was no reducer belt near the accidents r 38 There was a deceleration sign near the accidents r 39 There was no deceleration sign near the accidents r 40 There was a railway near the accidents r 41 There was no railway near the accidents r 42 There was a road safety measure near the accidents r 43 There was no road safety measure near the accidents r 44 There was a station near the accidents r 45 There was no station near the accidents r 46 There was a stop sign near the accidents.…”
Section: Data Preparation and Analysismentioning
confidence: 99%