Training and using neural networks to represent heuristic design knowledge
The detailed stage of structural design has benefited considerably from computer automation of the numerically intensive tasks of structural analysis, optimization and conformance checking using the procedural programming approach. Such an approach, however, does not allow for the representation and utilization of heuristic knowledge implicit in previous design solutions, which is often difficult or impossible to represent algorithmically. This paper describes how artificial neural networks can be trained to learn heuristic knowledge from previous design solutions and how this knowledge can then be applied to produce a solution to a similar design problem. Copyright (C) 1996 Civil-Comp Limited and Elsevier Science Limited
neural networks structural design knowledge representation