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Paper w78-1993-2-301:
Learning empirical knowledge to assist preliminary design

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Maher M L, Li H

Learning empirical knowledge to assist preliminary design

Abstract: The reuse of the experience of design and construction of a major project is ad hoc and depends on the individuals involved in the project being present on a similar project in the future. At the same time, the development of knowledge-based systems to support the design process requires the encoding of previous experience in a form that can be applied to future design projects. Machine learning techniques can be applied to automate the reuse of design experience and to facilitate the development of design knowledge bases. The application of machine learning techniques in a design domain requires the consideration of the representation of the learned design knowledge, that is, a target representation, as well as the content and form of the training data, or design examples. This paper proposes a target representation called a design concept and presents a methodology for learning design concepls from design examples. The method is illustrated by applying it to examples of bridge designs.

Keywords: machine learning; design; conceptual clustering; knowledge-based design


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Permission to reproduce these papers has been graciously provided by the National University of Singapore. The assistance of the editors, particularly Prof. Martin Betts, is gratefully appreciated.


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