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Perceptron Learning in Engineering Design
Author(s) -
ADELI H.,
YEH C.
Publication year - 1989
Publication title -
computer‐aided civil and infrastructure engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.773
H-Index - 82
eISSN - 1467-8667
pISSN - 1093-9687
DOI - 10.1111/j.1467-8667.1989.tb00026.x
Subject(s) - perceptron , computer science , multilayer perceptron , artificial intelligence , machine learning , domain (mathematical analysis) , tuple , control (management) , artificial neural network , mathematics , mathematical analysis , discrete mathematics
A model of machine learning in engineering design is presented based on the concept of self‐adjustment of internal control parameters and perceptron. A perceptron is defined as a four‐tuple entity which can answer either “yes” or “no” in the problem domain. The problem of structural design is cast in a form that can be described by a perceptron without hidden units. Some results from our experimentation are presented in tabular form. The paper is concluded by a comparison of perceptron and explanation‐based learning.