Abstract
This paper presents a nonlinear structural health assessing technique, based on an interactive data mining approach. A data mining control agent emulating cognitive process of human analyst is integrated in the data mining loop, analyzing and verifying the output of the data miner and controlling the data mining process to improve the interaction between human user and computer system. Additionally, an artificial neural network method, which is adopted as a core component of the proposed interactive data mining method, is evolved by adding a novelty detecting and retraining function for handling complicated nuclear power plant quake-proof data. To demonstrate how the proposed technique can be used as a powerful tool for assessment of structural status in nuclear power plant, quake-proof testing data has been applied.
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Shu, Y. (2007). Structural Health Assessing by Interactive Data Mining Approach in Nuclear Power Plant. In: Washio, T., Satoh, K., Takeda, H., Inokuchi, A. (eds) New Frontiers in Artificial Intelligence. JSAI 2006. Lecture Notes in Computer Science(), vol 4384. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69902-6_29
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DOI: https://doi.org/10.1007/978-3-540-69902-6_29
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