Debugging Finite Element Programs Input Data with Machine Learning

Yi‐Cherng ‐C Yeh, Yau‐Hwaug ‐H Kuo, Deh‐Shiu ‐S Hsu

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

Abstract: Debugging of the input data of a structural analysis program is a troublesome task which is heavily dependent on empirical knowledge. The paper describes an effort that applies machine learning to build an expert system for debugging faults in structural analysis program input data. ID3 decision tree induction algorithm is employed to build the automatic learning mechanism. This method Oflkrs an attractive potential for knowledge acquisition in the civil engineering domain in which expertise plays a dominant role. This paper is novel in at least three aspects: (1) machine learning is employed to build expert systems automatically; (2) a novel impurity function is proposed for splitting the decision tree; (3) a formulated comparison is proposed for evaluating learning results.

Original languageEnglish
Pages (from-to)223-233
Number of pages11
JournalComputer‐Aided Civil and Infrastructure Engineering
Volume7
Issue number3
DOIs
Publication statusPublished - 1992 May

All Science Journal Classification (ASJC) codes

  • Civil and Structural Engineering
  • Computer Science Applications
  • Computer Graphics and Computer-Aided Design
  • Computational Theory and Mathematics

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