[HTML][HTML] Advances, challenges, and future research needs in machine learning-based crash prediction models: A systematic review
Accurately modelling crashes, and predicting crash occurrence and associated severities
are a prerequisite for devising countermeasures and developing effective road safety …
are a prerequisite for devising countermeasures and developing effective road safety …
Classification of truck-involved crash severity: Dealing with missing, imbalanced, and high dimensional safety data
While the cost of road traffic fatalities in the US surpasses $240 billion a year, the availability
of high-resolution datasets allows meticulous investigation of the contributing factors to …
of high-resolution datasets allows meticulous investigation of the contributing factors to …
[HTML][HTML] Predictive evaluation of solar energy variables for a large-scale solar power plant based on triple deep learning forecast models
The advanced development of large-scale solar power plants (LSSPs) has made it
necessary to improve accurate forecasting models for the output of solar energy. Solar …
necessary to improve accurate forecasting models for the output of solar energy. Solar …
Severity prediction of highway crashes in Saudi Arabia using machine learning techniques
Kingdom of Among the G20 countries, Saudi Arabia (KSA) is facing alarming traffic safety
issues compared to other G-20 countries. Mitigating the burden of traffic accidents has been …
issues compared to other G-20 countries. Mitigating the burden of traffic accidents has been …
Interpretable dynamic ensemble selection approach for the prediction of road traffic injury severity: a case study of Pakistan's national highway N-5
Road traffic accidents are among the top ten major causes of fatalities in the world, taking
millions of lives annually. Machine-learning ensemble classifiers have been frequently used …
millions of lives annually. Machine-learning ensemble classifiers have been frequently used …
Prediction and interpretation of low-level wind shear criticality based on Its altitude above runway level: Application of Bayesian optimization–ensemble learning …
Low-level wind shear (LLWS) is a rare occurrence and yet poses a major hazard to the
safety of aircraft. LLWS event occurrence within 800 feet of the runway level are dangerous …
safety of aircraft. LLWS event occurrence within 800 feet of the runway level are dangerous …
Time-series prediction of intense wind shear using machine learning algorithms: a case study of Hong Kong international airport
Machine learning algorithms are applied to predict intense wind shear from the Doppler
LiDAR data located at the Hong Kong International Airport. Forecasting intense wind shear …
LiDAR data located at the Hong Kong International Airport. Forecasting intense wind shear …
Explainable Boosting Machine for Predicting Wind Shear-Induced Aircraft Go-around based on Pilot Reports
The go-around is a safety-critical procedure in civil aviation that is rarely executed but is
essential to avoid risky landings. Analyzing the factors that trigger go-around events can aid …
essential to avoid risky landings. Analyzing the factors that trigger go-around events can aid …
Prediction of aircraft go-around during wind shear using the dynamic ensemble selection framework and pilot reports
Pilots typically implement the go-around protocol to avoid landings that are hazardous due
to wind shear, runway excursions, or unstable approaches. Despite its rarity, it is essential …
to wind shear, runway excursions, or unstable approaches. Despite its rarity, it is essential …
Missed Approach, a Safety‐Critical Go‐Around Procedure in Aviation: Prediction Based on Machine Learning‐Ensemble Imbalance Learning
The final approach phase of an aircraft accounts for nearly half of all aviation incidents
worldwide due to low‐level wind shear, heavy downpours, runway excursions, and …
worldwide due to low‐level wind shear, heavy downpours, runway excursions, and …