Enhancing multi-layer perceptron [process control and modelling]

Author

Galán, R. ; Mariño, M. ; Jiménez, A.

Author_Institution

Dept. de Automatica, Ingenieria Electron. e Inf. Ind., Univ. Politecnica de Madrid, Spain

Volume

4

fYear

1994

fDate

27 Jun-2 Jul 1994

Firstpage

2661

Abstract

This paper present the results of a research on process modelling and control with neural networks, carried out in DISAM: Division de Ingenieria de Sistemas y Automatica, Universidad Politecnica de Madrid. The main goal of this research is the integration of neural networks in intelligent control applications of complex processes. A performance evaluation analyzing the number of delays, hidden layers and the quality of learning inputs is shown. Finally, the authors propose an enhancement of inputs with new information-products of inputs-to improve the accuracy of the neural network

Keywords

intelligent control; learning (artificial intelligence); multilayer perceptrons; neurocontrollers; process control; accuracy; delays; hidden layers; multi-layer perceptron; neural networks; performance evaluation; process control; process modelling; Adaptive control; Backpropagation; Delay; Industrial control; Intelligent control; Multi-layer neural network; Multilayer perceptrons; Neural networks; Performance analysis; Process control;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks, 1994. IEEE World Congress on Computational Intelligence., 1994 IEEE International Conference on

Conference_Location

Orlando, FL

Print_ISBN

0-7803-1901-X

Type

conf

DOI

10.1109/ICNN.1994.374642

Filename

374642