Object-oriented backpropagation and its application to structural design

Shih-Lin Hung, H. Adeli*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

58 Scopus citations

Abstract

A multilayer neural network development environment, called ANNDE, is presented for implementing effective learning algorithms for the domain of engineering design using the object-oriented programming paradigm. It consists of five primary components: learning domain, neural nets, library of learning strategies, learning process, and analysis process. These components have been implemented as five classes in two object-oriented programming languages C++ and G++. The library of learning strategies includes generalized delta rule with error backpropagation. Several examples are presented for learning in the domain of structural engineering.

Original languageEnglish
Pages (from-to)45-55
Number of pages11
JournalNeurocomputing
Volume6
Issue number1
DOIs
StatePublished - Feb 1994

Keywords

  • Backpropagation
  • object-oriented programming
  • structural design

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