APPLICATION OF MODIFIED ART2 ARTIFICIAL NEURAL NETWORK IN CLASSIFICATION OF STRUCTURAL MEMBERS

Abstract eng:
In this research the basic algorithm of ART2 neural network has been modified for proper and efficient classification of vectors. In the basic architecture of ART2, the length of vectors is neglected. This causes error in sorting; parallel vectors with different length are classified in the same category. To overcome this deficiency, an input virtual neuron is added to consider vector length. The modified architecture not only considers the similarity of vectors direction but also considers the magnitude of vectors in sorting. ART neural networks are classified as unsupervised learning nets, a method is presented for supervised learning of ART2 without general changes in the basic algorithm.

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