TL;DR
These findings suggest that arrival residuals are linked to voyage trajectories and environmental conditions, demonstrating that ensemble models can reduce the uncertainty of human-reported data.
Given the problems of non-stationary power time series, response lag, and amplified prediction errors due to sudden changes in wind direction under transitional meteorological conditions, this study proposes a wind power forecasting model that integrates multiscale time-series features, transition-aware attention mecha...
A novel machine learning (ML) framework for accurate real-time bus arrival time prediction integrates the ML model with a lightweight Dynamic Statistical Attention (DSA) technique. Real-time GPS data from Macao bus routes, synchronized with weather records, constitute the primary dataset. The DSA technique blends ML pr...
The sustained growth of urban populations has worsened chronic traffic congestion, with detrimental impacts on multiple dimensions of urban livability, including increased commute times, reduced road safety, and the degradation of local air quality. Thus, traffic speed prediction (TSP) is an important component of inte...
The scarcity of weather stations in many developing countries poses a significant obstacle to obtaining precise temperature data. Akwa Ibom State in Nigeria faces this challenge leading to reliance on satellite weather data (NASA POWER) and ground-truth measurements for temperature predictions. The study helps to predi...
The spread of the city, rising vehicle population, and the mounting demand for transportation have contributed to making traffic a major challenge for the modern cities. The effective prediction of the traffic flow is a key to enhancing the efficiency of transportation and alleviating congestion and to aid intelligent...
Precise prediction of vessel movements is crucial for effective maritime traffic monitoring and management. Automatic Identification System (AIS) data offer rich information for trajectory prediction but suffer from irregular sampling, missing values, noise, and transmission errors that complicate modeling. To addres...
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