Adapting conceptual clustering for preliminary structural design

Mary Lou Maher, Heng Li

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

3 Citations (Scopus)

Abstract

The use of conceptual clustering for knowledge acquisition can facilitate the development of a knowledge base in a domain where little formalized knowledge is really available. The limitations of current conceptual clustering techniques include a lack of accommodating varied attributes across training examples and a lack of learning associations among attributes within a cluster. A methodology is presented in which conceptual clustering is adapted to satisfy these limitations. A preliminary conceptual clustering technique is described where training examples are grouped according to similarity of attributes, rather than similarity or utility of similar values. Conceptual clustering is augmented by numerical methods for linear regression analysis and probabilistic approaches to pattern identification. The methodology is illustrated through its application to learning concepts for the preliminary design of bridges.
Original languageEnglish
Title of host publicationComputing in Civil and Building Engineering
PublisherPubl by ASCE
Pages1432-1439
Number of pages8
ISBN (Print)0872629155
Publication statusPublished - 1 Jan 1993
Externally publishedYes
EventProceedings of the 5th International Conference on Computing in Civil and Building Engineering - V-ICCCBE - Anaheim, CA, United States
Duration: 7 Jun 19939 Jun 1993

Conference

ConferenceProceedings of the 5th International Conference on Computing in Civil and Building Engineering - V-ICCCBE
CountryUnited States
CityAnaheim, CA
Period7/06/939/06/93

ASJC Scopus subject areas

  • Engineering(all)

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