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Found 4 papers, 0 papers with code
Integrated optimization of train timetables rescheduling and response vehicles on a disrupted metro line
Numerical cases of Beijing Metro Line 9 verify the efficiency and effectiveness of our proposed model, and results show that: (1) when occurring a disruption event during peak hours, the impact on the normal timetable is greater, and passengers in the direction with fewer train services are more affected; (2) if passengers stranded at the terminal stations of disruption area are not transported in time, they will rapidly increase at a speed of more than 300 passengers per minute; (3) compared with the fixed shortest path, using the response vehicles reduces the total travel time about 7%.
Enhancing Digital Health Services: A Machine Learning Approach to Personalized Exercise Goal Setting
This study aims to fill this gap by developing a machine learning algorithm that dynamically updates auto-suggestion exercise goals using retrospective data and realistic behavior trajectory.
Localized Adversarial Training for Increased Accuracy and Robustness in Image Classification
Today's state-of-the-art image classifiers fail to correctly classify carefully manipulated adversarial images.
Vision-based Traffic Flow Prediction using Dynamic Texture Model and Gaussian Process
The proposed method consists of three elemental operators, that are dynamic texture model based motion segmentation, feature extraction and Gaussian process (GP) regression.
