Machine Learning in Civil Engineering – Important Issues and Challenges

by Benoît Julien, Cent de Recherche Informatique de, Montreal, Montreal, Canada,

Document Type: Proceeding Paper

Part of: Computing in Civil Engineering

Abstract: In recent years, machine learning techniques have been applied to help overcome the knowledge acquisition bottleneck of knowledge-based systems in civil engineering. This paper identifies a number of important requirements of civil engineering machine learning problems. Preliminary results on several test cases serve to illustrate some of these key issues. The paper concludes on the central challenges for the successful automated acquisition of relevant civil engineering knowledge.

Subject Headings: Equipment and machinery | Knowledge-based systems | Data collection | Data processing | Expert systems | Interactive systems

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