TY - GEN
T1 - Auto-adapted ant colony optimization algorithm for wavelet network and its applications
AU - Shan, M. Y.
AU - Li, G.
PY - 2006
Y1 - 2006
N2 - In order to solve problems in wavelet network backward propagation, such as low-precision, slow learning process and easy convergence to the local minimum points, ant colony algorithm was modified. A wavelet network learning algorithm, which is based on modified auto-adapted ant colony algorithm, was put forward. Its application example of custom-made product cost estimation was given at last, which shows learning process and accuracy of the algorithm is better than others, and wavelet network training based on this algorithm has greater generality and better learning capacities.
AB - In order to solve problems in wavelet network backward propagation, such as low-precision, slow learning process and easy convergence to the local minimum points, ant colony algorithm was modified. A wavelet network learning algorithm, which is based on modified auto-adapted ant colony algorithm, was put forward. Its application example of custom-made product cost estimation was given at last, which shows learning process and accuracy of the algorithm is better than others, and wavelet network training based on this algorithm has greater generality and better learning capacities.
UR - http://www.scopus.com/inward/record.url?scp=34247227077&partnerID=8YFLogxK
U2 - 10.1109/ICMA.2006.257733
DO - 10.1109/ICMA.2006.257733
M3 - Conference contribution
AN - SCOPUS:34247227077
SN - 1424404665
SN - 9781424404667
T3 - 2006 IEEE International Conference on Mechatronics and Automation, ICMA 2006
SP - 2437
EP - 2442
BT - 2006 IEEE International Conference on Mechatronics and Automation, ICMA 2006
T2 - 2006 IEEE International Conference on Mechatronics and Automation, ICMA 2006
Y2 - 25 June 2006 through 28 June 2006
ER -