CFPs: Risk-Based Critical Valve Prioritization Using Machine Learning

The Risk-Based Prioritization of Critical Valves Using Limited Utility Data and Machine Learning project aims to improve critical valve management through data-driven risk assessment and machine learning. The project focuses on developing a data-efficient machine learning model to estimate the likelihood of valve failure using available utility data, including asset attributes, condition indicators, environmental factors,