Abstract
Developing mathematical models that represent physical devices is a difficult and time consuming task. In this paper, we present a hybrid approach to modeling that combines machine learning methods with knowledge from a human domain expert. Specifically, we propose a system for automatically revising an initial model provided by an expert with an equation discovery program that is tightly constrained by domain knowledge. We apply our system to learning an improved model of a battery on the International Space Station from telemetry data. Our results suggest that this hybrid approach can reduce model development time and improve model quality.
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© 2002 Springer-Verlag Berlin Heidelberg
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Bay, S.D., Shapiro, D.G., Langley, P. (2002). Revising Engineering Models: Combining Computational Discovery with Knowledge. In: Elomaa, T., Mannila, H., Toivonen, H. (eds) Machine Learning: ECML 2002. ECML 2002. Lecture Notes in Computer Science(), vol 2430. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36755-1_2
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DOI: https://doi.org/10.1007/3-540-36755-1_2
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