Chapter
Apr 26, 2012
Calibration of Lowry Model Using Immune Genetic Algorithm
Publication: Transportation and Development Innovative Best Practices 2008
Abstract
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.
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© 2008 American Society of Civil Engineers.
History
Published online: Apr 26, 2012
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ASCE Technical Topics:
- Algorithms
- Analysis (by type)
- Business management
- Calibration
- Case studies
- Employment
- Engineering fundamentals
- Forecasting
- Infrastructure
- Land use
- Mathematics
- Measurement (by type)
- Methodology (by type)
- Personnel management
- Practice and Profession
- Regression analysis
- Research methods (by type)
- Statistical analysis (by type)
- Statistics
- Urban and regional development
- Urban areas
- Validation
Authors
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Transportation College, Southeast University, Postcode: 210096, Nanjing, Jiangsu, China. E-mail: [email protected]
Transportation College, Southeast University, Postcode: 210096, Nanjing, Jiangsu, China. E-mail: [email protected]
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