Abstract
The extraction of knowledge from databases may be accomplished through the application of various machine learning and artificial intelligence methods. A hybrid approach is presented which uses a combination of case-based reasoning and artificial neural networks. The approach is illustrated through its application, in different ways, to two diverse practical domains: (i) the design of masonry panels, and (ii) the real-time forecasting of physical parameter values of the ocean. The results obtained to date are presented and the further continuation of the approach in the area of civil engineering design is discussed.
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Lees, B., Kumar, B., Mathew, A., Corchado, J., Sinha, B., Pedreschi, R. (1999). A Hybrid Case-Based Neural Network Approach to Scientific and Engineering Data Analysis. In: Milne, R.W., Macintosh, A.L., Bramer, M. (eds) Applications and Innovations in Expert Systems VI. Springer, London. https://doi.org/10.1007/978-1-4471-0575-6_18
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DOI: https://doi.org/10.1007/978-1-4471-0575-6_18
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