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

• Main Authors: Wei, Yuying, Law, Adrian Wing-Keung, Yang, Chun
• 其他作者: School of Civil and Environmental Engineering
• 格式: Article
• 語言: English
• 出版: 2024
• 主題: Engineering::Civil engineering; Data Assimilation; Missing Data
• 在線閱讀: https://hdl.handle.net/10356/173067

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...