Title :
A biologically inspired neural network for dynamic system optimization
Author :
Romero, Roseli Francelin ; Kacprzyk, Janusz ; Gomide, Fernando
Author_Institution :
ICMC-SCE, USP, Sao Carlos, Brazil
Abstract :
A neural network with a two-layer feedback topology and generalized recurrent neurons, for solving nonlinear discrete dynamic optimization problems is developed. The algorithm is based on R. Bellmann´s (1957) optimality principle and the interchange of information during synaptic chemical processing among neurons. The technique is applied to solve fuzzy decision making problems
Keywords :
decision support systems; fuzzy set theory; multilayer perceptrons; optimisation; recurrent neural nets; biologically inspired neural network; dynamic system optimization; fuzzy decision making problems; generalized recurrent neurons; information interchange; nonlinear discrete dynamic optimization problems; optimality principle; synaptic chemical processing; two-layer feedback topology; Decision making; Ear; Electronic mail; Iterative algorithms; Nerve fibers; Network topology; Neural networks; Neurofeedback; Neurons; Recurrent neural networks;
Conference_Titel :
Neural Information Processing, 1999. Proceedings. ICONIP '99. 6th International Conference on
Conference_Location :
Perth, WA
Print_ISBN :
0-7803-5871-6
DOI :
10.1109/ICONIP.1999.844680
