In order to investigate the suitability and potential benefits of applying land-use forecasting models in China, this paper presents an immune genetic algorithm for the calibration of Lowry model based on a maximum likelihood approach. The calibration procedure comprises three stages. In the first stage, an immune genetic algorithm is employed to calibrate the population and employment potentials, together with a coefficient associated with the travel impedance function in the study area. The second stage investigates the relationship between the calibrated potentials and various land-use variables, using a multivariate stepwise regression analysis. The third stage is model validation. A case study of Hu Zhou city, in Zhe Jiang province of China, was employed to demonstrate the performance of the proposed methodology. The results indicate that the calibrated Lowry model is acceptable for forecasting the future population and employment distribution in China.
Calibration of Lowry Model Using Immune Genetic Algorithm
First International Symposium on Transportation and Development Innovative Best Practices ; 2008 ; Beijing, China
2008-04-04
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
Calibration of Lowry Model Using Immune Genetic Algorithm
British Library Conference Proceedings | 2008
|Application of the Lowry Model to Land Use and Transportation Planning in Hong Kong
British Library Conference Proceedings | 1998
|Genetic Algorithm Approach in FRESIM Calibration
British Library Conference Proceedings | 1998
|