The present paper, describes the applications of two artificial neural networks, namely the backpropagation neural net (BPN) and the improved counterpropagation neural net (CPN) to the analysis and design of large scale space structures. Different aspects of these nets and parameters affecting the performance of each net is investigated. Two examples are studied, both of which are oriented towards structural optimization. A comparison is made on the performance of these nets The improved CPN is trained faster than BPN, especially when large scale problems are involved. The responses of BPN and improved CPN are compared for the same input.
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