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The increasing use of renewable energy in buildings requires optimization of building demand flexibility to reduce energy costs and carbon emissions. Nevertheless, the optimization process is generally challenging that needs to consider the on-site intermittent energy supply, dynamic building energy demand, and proper utilization of energy storage systems. Leveraging the growing availability of operational data in buildings, data-driven strategies such as reinforcement learning (RL) have emerged as effective approaches to optimizing building demand flexibility. However, training a reliable RL ...

Private health insurance (PHI) companies have a growing claims dataset that could be used to identify leading indicators for hospitalisation. This study is primarily focused on addiction, mental health, obesity and musculoskeletal disorders disease groups. Leading indicator analysis employed three methods: association rule mining, sequential rule mining, and a heuristic method. Evaluating program effectiveness was performed using propensity score-based matching. PHI professionals were working alongside the research to aid in comprehending data and essential information from a PHI perspective. ...