학술논문
Parameter reduction method for transport network control
Document Type
TEXT
Author
Source
Neural network world: international journal on neural and mass-parallel computing and information systems | 2001 Volume:11 | Number:1
Subject
Language
English
Abstract
The main goal of this paper is to use traíRc data measured automatically by inductive loops, reduce the dimensionality of measured data vector and apply the reduced data vector for imitation of the traffic operator’s behaviour. The feature vector’s dimensionality is reduced both by Fisher criterion and truncated SVD (singular value decornposition) rnethods. For the operator’s imitation the Laplace classifier is applied.