Ahmed Farhad Skandary (Avtor), Nima Dadashzadeh (Avtor), Marijan Žura (Avtor)

Povzetek

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.

Ključne besede

differential evolution;multi-objective optimization;calibration;LUTI;land-use;transport modelling;TRANUS;

Podatki

Jezik: Angleški jezik
Leto izida:
Tipologija: 1.01 - Izvirni znanstveni članek
Organizacija: UL FGG - Fakulteta za gradbeništvo in geodezijo
UDK: 004:656.1
COBISS: 91423491 Povezava se bo odprla v novem oknu
ISSN: 2169-3536
Št. ogledov: 92
Št. prenosov: 16
Ocena: 0 (0 glasov)
Metapodatki: JSON JSON-RDF JSON-LD TURTLE N-TRIPLES XML RDFA MICRODATA DC-XML DC-RDF RDF

Ostali podatki

Sekundarni jezik: Angleški jezik
Vrsta dela (COBISS): Članek v reviji
Strani: [11] f.
Letnik: ǂLetn. ǂ9
Zvezek: ǂšt. ǂ167004
Čas izdaje: 27. dec. 2021
DOI: 10.1109/ACCESS.2021.3135949
ID: 14768482