Abstract
During the last thirty years there has been much research effort in regional science
devoted to modelling interactions over geographic space. Theoretical approaches for
studying these phenomena have been modified considerably. This paper suggests a 'new
modelling approach, based upon a general nested sigmoid neural network model. Its
feasibility is illustrated in the context of modelling interregional telecommunication traffic in
Austria and its performance is evaluated in comparison with the classical regression
approach of the gravity type. The application of this neural network approach may be
viewed as a three-stage process. The first stage refers to the identification of an
appropriate network from the family of two-layered feedforward networks with 3 input
nodes, one layer of (sigmoidal) intermediate nodes and one (sigmoidal) output node
(logistic activation function). There is no general procedure to address this problem. We
solved this issue experimentally. The input-output dimensions have been chosen in order
to make the comparison with the gravity model as close as possible. The second stage
involves the estimation of the network parameters of the selected neural network model.
This is perlormed via the adaptive setting of the network parameters (training, estimation)
by means of the application of a least mean squared error goal and the error back
propagating technique, a recursive learning procedure using a gradient search to
minimize the error goal. Particular emphasis is laid on the sensitivity of the network
perlormance to the choice of the initial network parameters as well as on the problem of
overlitting. The final stage of applying the neural network approach refers to the testing of
the interregional teletraffic flows predicted. Prediction quality is analysed by means of two
perlormance measures, average relative variance and the coefficient of determination, as
well as by the use of residual analysis. The analysis shows that the neural network model
approach outperlorms the classical regression approach to modelling telecommunication
traffic in Austria. (authors' abstract)
devoted to modelling interactions over geographic space. Theoretical approaches for
studying these phenomena have been modified considerably. This paper suggests a 'new
modelling approach, based upon a general nested sigmoid neural network model. Its
feasibility is illustrated in the context of modelling interregional telecommunication traffic in
Austria and its performance is evaluated in comparison with the classical regression
approach of the gravity type. The application of this neural network approach may be
viewed as a three-stage process. The first stage refers to the identification of an
appropriate network from the family of two-layered feedforward networks with 3 input
nodes, one layer of (sigmoidal) intermediate nodes and one (sigmoidal) output node
(logistic activation function). There is no general procedure to address this problem. We
solved this issue experimentally. The input-output dimensions have been chosen in order
to make the comparison with the gravity model as close as possible. The second stage
involves the estimation of the network parameters of the selected neural network model.
This is perlormed via the adaptive setting of the network parameters (training, estimation)
by means of the application of a least mean squared error goal and the error back
propagating technique, a recursive learning procedure using a gradient search to
minimize the error goal. Particular emphasis is laid on the sensitivity of the network
perlormance to the choice of the initial network parameters as well as on the problem of
overlitting. The final stage of applying the neural network approach refers to the testing of
the interregional teletraffic flows predicted. Prediction quality is analysed by means of two
perlormance measures, average relative variance and the coefficient of determination, as
well as by the use of residual analysis. The analysis shows that the neural network model
approach outperlorms the classical regression approach to modelling telecommunication
traffic in Austria. (authors' abstract)
| Original language | English |
|---|---|
| Place of Publication | Vienna |
| Publisher | WU Vienna University of Economics and Business |
| Publication status | Published - 1 Mar 1994 |
Publication series
| Name | Discussion Papers of the Institute for Economic Geography and GIScience |
|---|---|
| No. | 38/94 |
WU Working Paper Series
- Discussion Papers of the Institute for Economic Geography and GIScience