From the 1 of 5 linked papers with an AI index.
5 papers
Learning-based Probabilistic Load Forecasting with Post-hoc and In-model Uncertainty
Sarah Al-Shareeda, Gulcihan Ozdemir, Heung Seok Jeon
The paper proposes a one‑day‑ahead probabilistic load forecasting framework for smart buildings that handles missing input features by either post‑hoc residual quantiles or integra…
Would Learning Help? Adaptive CRC-QC-LDPC Selection for Integrity in 5G-NR V2X
Sarah Al-Shareeda, Gulcihan Ãzdemir, Arouj Fatima +4
Vehicle-to-everything (V2X) communications impose stringent physical-layer integrity requirements, particularly under short-packet transmission and mobility-induced channel variati…
A Lightweight DL Model for Smart Grid Power Forecasting with Feature and Resolution Mismatch
Sarah Al-Shareeda, Gulcihan Ozdemir, Heung Seok Jeon +1
How can short-term energy consumption be accurately forecasted when sensor data is noisy, incomplete, and lacks contextual richness? This question guided our participation in the \…
Accurate AI-Driven Emergency Vehicle Location Tracking in Healthcare ITS Digital Twin
Sarah Al-Shareeda, Yasar Celik, Bilge Bilgili +2
Creating a Digital Twin (DT) for Healthcare Intelligent Transportation Systems (HITS) is a hot research trend focusing on enhancing HITS management, particularly in emergencies whe…
AI-based traffic analysis in digital twin networks
Sarah Al-Shareeda, Khayal Huseynov, Lal Verda Cakir +3
In today's networked world, Digital Twin Networks (DTNs) are revolutionizing how we understand and optimize physical networks. These networks, also known as 'Digital Twin Networks…