TY - GEN
T1 - A combined genetic algorithm and orthogonal transformation for designing feedforward neural networks
AU - Xu, Jinhua
AU - Lu, Yue
AU - Ho, Daniel W.C.
PY - 2007
Y1 - 2007
N2 - In this paper, a hybrid algorithm is proposed for designing feedforward neural networks. A genetic algorithm is used to tune the connections and parameters between the input layer and the hidden layer, and orthogonal transformation is applied to tune the connections and parameters between the hidden layer and the output layer. In this way, both the structure and parameters of a neural network can be optimized efficiently. Simulations are presented to demonstrate the effectiveness of the proposed approach.
AB - In this paper, a hybrid algorithm is proposed for designing feedforward neural networks. A genetic algorithm is used to tune the connections and parameters between the input layer and the hidden layer, and orthogonal transformation is applied to tune the connections and parameters between the hidden layer and the output layer. In this way, both the structure and parameters of a neural network can be optimized efficiently. Simulations are presented to demonstrate the effectiveness of the proposed approach.
UR - https://www.scopus.com/pages/publications/38049084870
U2 - 10.1109/ICNC.2007.13
DO - 10.1109/ICNC.2007.13
M3 - 会议稿件
AN - SCOPUS:38049084870
SN - 0769528759
SN - 9780769528755
T3 - Proceedings - Third International Conference on Natural Computation, ICNC 2007
SP - 10
EP - 14
BT - Proceedings - Third International Conference on Natural Computation, ICNC 2007
T2 - 3rd International Conference on Natural Computation, ICNC 2007
Y2 - 24 August 2007 through 27 August 2007
ER -