Real-time Trajectory Optimization (RTOP) is a machine learning-based flight path optimization framework that automatically performs in-flight re-planning continuously with the latest weather information. The framework leverages three core algorithms: (1) a supervised learning algorithm to...

Missing data can significantly impact dataset integrity and suitability, leading to unreliable statistical results, distortions, and poor decisions. The presence of missing values in data introduces inaccuracies in clustering and classification and compromises the reliability and validity of...

Many forecasting methods perform poorly when dealing with intermittent demand patterns and large variations in demand quantity. The presence of significant fluctuations within the time series, coupled with a substantial proportion of zero observations, complicates the extraction of trend and...

Data Envelopment Analysis (DEA), Multi-criteria Decision Analysis (MCDA), and Cluster Analysis (CA) are techniques widely used to help decision-makers determine the solution to problems with multiple and often conflicting criteria. This study presents a comprehensive review of the literature on...

The communities in a network have distinct characteristics and interrelationships. Community discovery methods based on node embedding and deep learning have surpassed spectral clustering and statistical inference as the preferred methods for handling high-dimensional network data. Community...

Analyzing the flow of vehicles within a metropolitan area is essential to understand traffic congestion better and evaluate urban mobility for more environmentally and sustainable targets. This study uses real-time big data to conduct a spatiotemporal analysis of traffic congestion patterns in...