Parallel modelling and neural networks: An overview for transportation land use systems

被引：20

作者：

Rodrigue, JP ^{[1
]}

机构：

[1] Univ Montreal, Ctr Res Transportat, Quebec City, PQ H3C 3J7, Canada

来源：

TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES | 1997年 / 5卷 / 05期

关键词：

transportation; land use; modelling; parallel distributed processing; neural networks;

D O I：

10.1016/S0968-090X(97)00014-4

中图分类号：

U [交通运输];

学科分类号：

08 ; 0823 ;

摘要：

We provide in this conceptual paper an overview of a parallel transportation/land use modelling environment. We argue that sequential urban modelling does not well represent complex urban dynamics. Instead, we suggest a parallel distributed processing structure composed of processors and links between processors. Each processor is a set of neurons and weights between neurons forming a neural network. For spatial systems neural networks have two main paradigms which are processes simulation and pattern association. Parallel distributed processing offers a new methodology to represent the relational structure between elements of a transportation/land use system and thus helping to model those systems. We also provide a set of advantages, drawbacks and some research directions about the usage of neural networks for spatial analysis and modelling. (C) 1997 Elsevier Science Ltd. All rights reserved.

引用

页码：259 / 271

页数：13

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