Partial Least Squares Regression Based Cellular Automata Model for Simulating Complex Urban Systems
نویسندگان
چکیده
A Cellular Automata model based on Partial Least Squares Approaches is proposed for simulating complex urban systems. The core part of Geo-CA model is the transition rules and a mass of independent spatial variables are involved in the process of creating CA model. Studies have focused on eliminating correlation using Multi-Criteria Evaluation (MCE) and Principal Component Analysis (PCA), but there is no a thoroughly solution with a reasonable result for the issue. Using Partial Least Squares Regression integrated with Geo-CA and GIS, a novel CA model is created for better urban expansion simulation. The model has been successfully applied to the simulation of urban development in Jiading District, Shanghai. * Corresponding author: [email protected]; phone +86-(0)21-65988851.
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تاریخ انتشار 2008