Data assimilation with missing data in nonstationary environments for probabilistic machine learning models

• Main Authors: Wei, Yuying, Law, Adrian Wing-Keung, Yang, Chun
• Other Authors: School of Civil and Environmental Engineering
• Format: Article
• Language: English
• Published: 2024
• Subjects: Engineering::Civil engineering; Data Assimilation; Missing Data
• Online Access: https://hdl.handle.net/10356/173067
• Institution: Nanyang Technological University

In this study, we further develop the data assimilation framework proposed for probabilistic Machine Learning (ML) models, named Probabilistic Optimal Interpolation (POI), in nonstationary environments with missing data which are common in real-world situations. The dataset is based on a multi-scale...