This paper presents a novel bi-level machine learning framework enhanced with outlier removal and intra–extra joint optimisation for predicting the incident ...

May 10, 2022 · This paper presents a novel bi-level machine learning framework enhanced with outlier removal and intra-extra joint optimisation for predicting ...

Grigorev et al. proposed a new intra-extra joint optimization machine learning (IEO-ML) approach and verified that 40-45 min is the best threshold for ...

This is the code for the paper: Incident duration prediction using a bi-level machine learning framework with outlier removal and intra–extra joint ...

This paper proposes a bi-level framework for predicting the accident duration on arterial road networks in Sydney, based on operational requirements of ...

Predicting the duration of traffic incidents is a challenging task due to the stochastic nature of events. The ability to accurately predict how long ...

Chen, Incident duration prediction using a bi-level machine learning framework with outlier removal and intra–extra joint optimisation,. Transp. Res. Part C ...

This study gathered accident duration, road conditions, and meteorological data from a database of traffic accidents to check the feasibility of a traffic ...

Incident duration prediction using a bi-level machine learning framework with outlier removal and intra–extra joint optimisation. A Grigorev, AS Mihaita, S ...

Incident duration prediction using a bi-level machine learning framework with outlier removal and intra–extra joint optimisation, Transportation Research ...