Title :
Neural network based system modeling
Author :
Vanlandingham, H.F. ; Choi, J.Y.
Author_Institution :
Bradley Dept. of Electr. Eng., Virginia Polytech. Inst. & State Univ., Blacksburg, VA, USA
Abstract :
A method of using multi-layer perceptrons (MLPs) for modeling complex nonlinear systems is investigated. The importance of pre-processing is crucial to the modeling stage. This includes classifying input/output data into different categories for training-data selection, as well as extracting key features of the data. In this paper a prototype problem, an inverted pendulum system, is simulated as a physical system to be identified. The discussion focuses on this problem although the ideas are generic
Keywords :
large-scale systems; modelling; multilayer perceptrons; nonlinear systems; complex nonlinear systems; inverted pendulum system; multi-layer perceptrons; neural network based system modeling; training-data selection; Data mining; Feature extraction; Linear systems; Mathematical model; Modeling; Multilayer perceptrons; Neural networks; Neurons; Nonlinear dynamical systems; Nonlinear systems;
Conference_Titel :
Systems, Man and Cybernetics, 1995. Intelligent Systems for the 21st Century., IEEE International Conference on
Conference_Location :
Vancouver, BC
Print_ISBN :
0-7803-2559-1
DOI :
10.1109/ICSMC.1995.538484
