The work represents an artificial neural networkf01· recognitionof county centre post codes. The neural networkPOSTKLAS se1ves as the classification system for the sorting oftwo-digit address data. The de1·eloped model represents atwo-layer network which learns by using backpropagation algorithm.The method of address data recording in the model hasbeen presented. By analysing the sorting results the possibilitywas determined of applying the developed neural network forrecognition even in cases of distorted input pal/erns. The modellingwas done by means of Mat/ab programming ~ystem.
H. Demuth, M. Beale, Neural Network Too/box For Use
with Matlab, User's guide, MathWorks, 1993.
H. Gold, Z. Kavran, D. Kovacevic, 'Recognition of
geometrical properties of traffic signs with artificial neural
network', Suvremeni promet - Proceedings of the 5th
International Symposium Organisation and Safety in
Traffic, Opatija, 1997, Vol. 17, No. 3-4, pp. 330-334 (in
Croatian)
H. Gold, 'Neural networks in traffic and transport'',
Teaching material and instructions for omputer practice,
Fakultet prometnih znanosti, Zagrcb, 1998, p. 107
(in Croatian)
D. Hladnik, 'Automatic reading of address data',
HP-Journal Hrvatske poste, No. 4/99, pp. 15-17 (in
Croatian)
P. D. Wasserman, Neural Computing: The01y and Practice,
Van Nostrand Reinhold, New York, 1985.
Guest Editor: Eleonora Papadimitriou, PhD
Editors: Dario Babić, PhD; Marko Matulin, PhD; Marko Ševrović, PhD.
The mission of our journal is to provide high quality communication of research results, which is crucial for the effectiveness of scientific research, the promotion of scientific information, new ideas, and original research in the field of traffic and transportation engineering.
1848-4069
0353-5320
Proud publisher
Accelerating Discoveries in Traffic Science |
2024 © Promet - Traffic&Transportation journal
