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The Nuclear Energy Agency (NEA) is a specialized agency within the Organization for Economic Co-operation and Development (OECD). The International Fire Data Exchange Project (OECD FIRE) was designed by the NEA to encourage multilateral co-operation in the collection and analysis of data relating to fire events in nuclear power plants. We used Python advanced software to analyze the data related to CANDU reactor plants in Canada from the OECD FIRE Database, while providing weighting factors/percentage tables to be used in CANDU Fire probabilistic risk assessment analysis. We also used 5 different time-series methods to predict future potential fires in CANDU reactors, compared the results from different methods, and identified the best method to predict future fires in CANDU power plants.
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Papers that cite the same references — the relational fallback while embeddings are still backfilling.
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