A Novel LUTI Model Calibration Using Differential Evolution Algorithm

Ahmad Farhad Skandary

doi:10.1109/ACCESS.2021.3135949

2021-01-01

Ahmad Farhad Skandary *

Nima Dadashzadeh

Marijan Žura

DOI：10.1109/ACCESS.2021.3135949

原文链接

摘要

En 中文

LUTI (Land-Use and Transportation Interaction) models are decision-making aid tools that simulate complex dynamic bilateral feedback between transportation and land-use models within a territory. Although calibration (parameter estimation) is a crucial requirement of LUTI models, fully automated approaches with the usage of multi-objective functions have not been fully addressed. To address this limitation, a generic calibration approach is proposed for the parameters of the land-use model using a differential evolution algorithm. A global sensitivity analysis was performed to identify the most important land-use model parameters. These parameters were then calibrated using the differential evolution algorithm with the Root Mean Square Error (RMSE) and Mean Absolute Normalized Error (MANE) as multi-objective functions. Five key capabilities are provided in the suggested technique for calibration of LUTI models including 1) global estimation rather than local estimation, 2) consideration of multi-objective functions, 3) continuously improving the results, 4) easily adaptability, and 5) involving multi parameters in the calibration process. The TRANUS land-use model was used to test the performance of the suggested calibration technique. The validation and consolidation of the approach were tested based on convergence, minimization of errors, and modeled/observed data ratio by comparing with the genetic algorithm and particle swarm optimization techniques. Using the deferential evaluation algorithm, the suggested approach outperformed both genetic and particle swarm optimization techniques and provided the most stable and diverse solutions.

Keyword:

Calibration

Transportation

Estimation

Analytical models

Sensitivity analysis

Optimization

Numerical models

Differential evolution

multi-objective optimization

calibration

LUTI