Neural Networks in Modelling Maintenance Unit Load Status

  • Anđelko Vojvoda
  • Hrvoje Gold
Keywords: Artificial Intelligence, expert systems, neural networks, maintenance, logistic analysis

Abstract

This paper deals with a way of applying a neural networkfor describing se1vice station load in a maintenance unit. Dataacquired by measuring the workload of single stations in amaintenance unit were used in the process of training the neuralnetwork in order to create a model of the obse1ved system.The model developed in this way enables us to make more accuratepredictions over critical overload. Modelling was realisedby developing and using m-functions of the Matlab software.

References

C. J, Haris, Advances in Intelligent Control. Taylor&

Francis Ltd., London, 1994.

H. Gold, Neuronske mreie u prometu i transportu (Neural

networks in Traffic and Transport), Authorised Lectures.

FPZ, Zagreb, 1998. (in Croatian)

H. Gold, Neuronske mreie u prometu i transportu, Upute

za vjetbe na racunalu. FPZ, Zagreb, 1998. (in Croatian)

D.P. Pham, X. Liu, Neural networks for identification,

prediction and control. Springer-Verlag, London, 1995.

V. Ceric, Simulacijsko modeliranje, Skolska knjiga, Zagreb,

(in Croatian)

B. Novakovic, Umjetna inteligencija i proizvodni sustavi.

FSB, Zagreb, 1998. (in Croatian)

P. Sikavica, H. Skoko, D. Tipuric, M. Dalic, Poslmmo

odlucivanje. Informator, Zagreb 1994. (in Croatian)

J, L. McClelland, D. E. Rumelhart, Explorations in

Parallel Distributed Processing, Bradford Book, Cambridge,

H. Demuth, M. Beale, Neural Network Toolbox For Use

with Matlab, User's guide, Math Works, 1992.

V. Ziljak, Modeliranje i simuliranje. Skolska knjiga,

Zagreb 1982. (in Croatian)

How to Cite
1.
Vojvoda A, Gold H. Neural Networks in Modelling Maintenance Unit Load Status. Promet [Internet]. 1 [cited 2024Nov.23];14(2):85-1. Available from: https://traffic.fpz.hr/index.php/PROMTT/article/view/851
Section
Older issues