TY - GEN
T1 - Training neural networks using taguchi methods
T2 - 15th International Conference on Artificial Neural Networks: Biological Inspirations - ICANN 2005
AU - Viswanathan, Alagappan
AU - MacLeod, Christopher
AU - Maxwell, Grant
AU - Kalidindi, Sashank
PY - 2005
Y1 - 2005
N2 - Taguchi Methods (and other orthogonal arrays) may be used to train small Artificial Neural Networks very quickly in a variety of tasks. These include, importantly, Control Systems. Previous experimental work has shown that they could be successfully used to train single layer networks with no difficulty. However, interaction between layers precluded the successful reliable training of multi-layered networks. This paper describes a number of successful strategies which may be used to overcome this problem and demonstrates the ability of such networks to learn non-linear mappings.
AB - Taguchi Methods (and other orthogonal arrays) may be used to train small Artificial Neural Networks very quickly in a variety of tasks. These include, importantly, Control Systems. Previous experimental work has shown that they could be successfully used to train single layer networks with no difficulty. However, interaction between layers precluded the successful reliable training of multi-layered networks. This paper describes a number of successful strategies which may be used to overcome this problem and demonstrates the ability of such networks to learn non-linear mappings.
UR - https://www.scopus.com/pages/publications/33646242029
UR - https://www.scopus.com/pages/publications/33646242029#tab=citedBy
M3 - Conference contribution
AN - SCOPUS:33646242029
SN - 3540287558
SN - 9783540287551
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 103
EP - 108
BT - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Y2 - 11 September 2005 through 15 September 2005
ER -