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Evidence-based managerial decision-making with machine learning: The case of Bayesian inference in aviation incidents
Understanding the factors behind aviation incidents is essential, not only because of the
lethality of the accidents but also the incidents' direct and indirect economic impact. Even …
lethality of the accidents but also the incidents' direct and indirect economic impact. Even …
Crash severity analysis of vulnerable road users using machine learning
Road crash fatality is a universal problem of the transportation system. A massive death toll
caused annually due to road crash incidents, and among them, vulnerable road users (VRU) …
caused annually due to road crash incidents, and among them, vulnerable road users (VRU) …
[HTML][HTML] Develo** new hybrid grey wolf optimization-based artificial neural network for predicting road crash severity
With more cars on the road and an increasing travel rate, one of the main issues in
transportation engineering is how to make roads safe. The evaluation of the level of road …
transportation engineering is how to make roads safe. The evaluation of the level of road …
Addressing endogeneity in modeling speed enforcement, crash risk and crash severity simultaneously
Speeding is one of the major significant causes of high crash risk and the associated injury
severity outcomes. To combat such significant safety concerns, a speed limit enforcement …
severity outcomes. To combat such significant safety concerns, a speed limit enforcement …
Road accident analysis with data mining approach: evidence from Rome
Nowadays, road accident is one of the main causes of mortality worldwide. Then, measures
are required to reduce or mitigate the accident impacts. The identification of the most …
are required to reduce or mitigate the accident impacts. The identification of the most …
Advancing proactive crash prediction: A discretized duration approach for predicting crashes and severity
Driven by advancements in data-driven methods, recent developments in proactive crash
prediction models have primarily focused on implementing machine learning and artificial …
prediction models have primarily focused on implementing machine learning and artificial …
A new econometric approach for modeling several count variables: a case study of crash frequency analysis by crash type and severity
There is limited adoption of research modeling crash severity frequency considering
different crash types due to the challenge associated with analyzing large number of …
different crash types due to the challenge associated with analyzing large number of …
Factors affecting injury severity in motorcycle crashes: Different age groups analysis using Catboost and SHAP techniques
Objective Motorcycle crashes often result in severe injuries on roads that affect people's
lives physically, financially, and psychologically. These injuries could be notably harmful to …
lives physically, financially, and psychologically. These injuries could be notably harmful to …
Integrating safety into the fundamental relations of freeway traffic flows: A conflict-based safety assessment framework
Numerous statistical and data-driven modeling frameworks have estimated rear-end
crashes and crash-prone events from macroscopic traffic states which are at the heart of …
crashes and crash-prone events from macroscopic traffic states which are at the heart of …
Analysis of injuries and deaths from road traffic accidents in Iran: bivariate regression approach
Backgrounds This study aims to estimate and compare the parameters of some univariate
and bivariate count models to identify the factors affecting the number of mortality and the …
and bivariate count models to identify the factors affecting the number of mortality and the …