Application of neural networks to group technology
Thomas P. Caudell, Scott D. G. Smith, Greshma Johnson, Donald C. Wunsch · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1991
ormance of this compressed algorithm is compared to that of the regular algorithm on real engineering designs anda significant savings in memory storage as well as a speed up in execution is observed. In addition, we will describe aneural database system under development. This system demonstrates the feasibility of training an ART-i networkto first cluster designs into families, and then to recall the family when presented a similar design. This application isoflarge practical value to industry, making it possible to avoid duplication of design efforts.