A Modular Modelling Framework for Hypotheses Testing in the Simulation of Urbanisation

Systems

Clémentine Cottineau¹  Romain Reuillon²  Paul Chapron²  Sstien Rey-Coyrehourcq²  Denise Pumain²  Koen H. van Dam³ 

[1] Centre for Advanced Spatial Analysis, University College London, London W1T 4TJ, UK;UMR 8504 Géographie-cités and The Institute of Complex Systems (ISC-PIF), Paris 75006, France;id="af1-systems-03-00348">1Centre for Advanced Spatial Analysis, University College London, London W1T 4TJ,

关键词: system of cities;    ABM;    simulation;    former soviet union;    equifinality;    multimodelling;   

DOI  :  10.3390/systems3040348

来源: mdpi

【 摘 要 】

In this paper, we present a modelling experiment developed to study systems of cities and processes of urbanisation in large territories over long time spans. Building on geographical theories of urban evolution, we rely on agent-based models to 1) formalise complementary and alternative hypotheses of urbanisation and 2) explore their ability to simulate observed patterns in a virtual laboratory. The paper is therefore divided into two sections : an overview of the mechanisms implemented to represent competing hypotheses used to simulate urban evolution; and an evaluation of the resulting model structures in their ability to simulate—efficiently and parsimoniously—a system of cities (between 1000 and 2000 cities in the Former Soviet Union) over several periods of time (before and after the crash of the USSR). We do so using a modular framework of model-building and evolutionary algorithms for the calibration of several model structures. This project aims at tackling equifinality in systems dynamics by confronting different mechanisms with similar evaluation criteria. It enables the identification of the best-performing models with respect to the chosen criteria by scanning automatically the parameter space along with the space of model structures (the different combinations of mechanisms).

【 授权许可】

CC BY   
© 2015 by the authors; licensee MDPI, Basel, Switzerland.