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Recent Advances in Robotic Systems
Recent Advances in Robotic Systems
Shipping market forecasting by forecast combination mechanism
Dynamic "Standing Orders" for Autonomous Navigation System by means of Machine Learning
Microscopic modeling of cyclists on off-street paths: a stochastic imitation learning approach
A bibliometric analysis and review on reinforcement learning for transportation applications
Application of algorithmic models of machine learning to the freight transportation process
Calibrating microscopic traffic simulators using machine learning and particle swarm optimization
Application of mayfly algorithm for prediction of removed sediment in hydro-suction dredging systems
Annals of Scientific Society for Assembly, Handling and Industrial Robotics 2022
Annals of Scientific Society for Assembly, Handling and Industrial Robotics 2022
Using reinforcement learning to minimize taxi idle times
Annals of Scientific Society for Assembly, Handling and Industrial Robotics 2021
Traffic volume prediction on low-volume roadways: a Cubist approach
Integration of machine learning and statistical models for crash frequency modeling
Incorporating congestion patterns into spatio-temporal deep learning algorithms
Framework for development of the Scheduler for Activities, Locations, and Travel (SALT) model
Integrating data-driven and simulation models to predict traffic state affected by road incidents
Estimating the effect of biofouling on ship shaft power based on sensor measurements
Prediction of extent of damage in vehicle during crash using improved XGBoost model
Method for automated detection of outliers in crash simulations
GraphCast for solving the air transportation nexus among safety, efficiency, and resilience
Assessing influential factors for lane change behavior using full real-world vehicle-by-vehicle data
Sharkeye: Real-Time Autonomous Personal Shark Alerting via Aerial Surveillance
Predicting incident duration using random forests
Estimating cycle-level real-time traffic movements at signalized intersections
Arterial corridor travel time prediction under non-recurring conditions
Probabilistic traffic breakdown forecasting through Bayesian approximation using variational LSTMs
UAV-Based Wetland Monitoring: Multispectral and Lidar Fusion with Random Forest Classification
Predicting the traction power of metropolitan railway lines using different machine learning models
Studying the capabilities of the analytical system based on the machine learning method
Using supervised machine learning algorithms in pavement degradation monitoring
Driver Identification with OBD-II Public Data
An Effort to Detect Vehicle Drivers Drowsy State Based on the Speed Analysis
Bayesian and machine learning-based fault detection and diagnostics for marine applications
Driver’s black box: a system for driver risk assessment using machine learning and fuzzy logic