A Modified Genetic Algorithm for Neurocontrollers

Cited 0 time in webofscience Cited 0 time in scopus
  • Hit : 551
  • Download : 795
Genetic algorithms are getting more popular nowadays because of their simplicity and robustness. Genetic algorithms are global search techniques for optimizations and many other problems. A feed-forward neural network that is widely used in central applications usually learns by back propagation algorithm (BP). However, when there exist certain constraints, BP cannot be applied. We apply a genetic algorithm to such a case. To improve hill-climbing capability and speed up the convergence, we propose a modified genetic algorithm (MGA). The validity and efficiency of the proposed algorithm. MGA are shown by various simulation examples of system identification and nonlinear system control such as cart-pole systems and robot manipulators
Publisher
IEEE
Issue Date
1996
Keywords

Genentic algorithm; neurocontroller

Citation

Evolutionary Computation, 1995., IEEE International Conference on, Volume: 1, On page(s): 306-311

ISBN
0-7803-2759-4
DOI
10.1109/ICEC.1995.489164
URI
http://hdl.handle.net/10203/8305
Appears in Collection
EE-Conference Papers(학술회의논문)
Files in This Item
IntC_044.pdf(508.22 kB)Download

qr_code

  • mendeley

    citeulike


rss_1.0 rss_2.0 atom_1.0