This paper presents a neural network approach for building Neuroform, a computer system that provides the selection of vertical formwork systems for a given building site. The reasons for choosing a neural network approach instead of a traditional expert system are discussed. The selection of an appropriate neural network model, its architecture, representation of the network training examples, and the network training procedure are described. The details of the user interaction with the trained neural network system are presented. The performance of Neuroform is validated comparing its recommendations with that of Wallform, a rule-based expert system for vertical formwork selection. A statistical hypothesis test, conducted on the recommendations of Neuroform when partial inputs are given, demonstrates the system’s fault-tolerant and generalization properties.
|Original language||English (US)|
|Number of pages||22|
|Journal||Journal of Computing in Civil Engineering|
|State||Published - Apr 1992|
All Science Journal Classification (ASJC) codes
- Civil and Structural Engineering
- Computer Science Applications