You're currently viewing an old version of this dataset. To see the current version, click here.

Parameter Optimization for the HYPE model with Shuffled Frog Leaping Algorithm (SFLA)

Python scripts for controlling parameter optimization for the hydrological model HYPE. The scripts can be used to optimize model parameters with the Shuffled Frog Leaping Algorithm (SFLA). Additionally, there is a modification of the Differential Evolution Markov Chain (DEMC) algorithm, which has been previously applied for HYPE. In this first version, all parameters of SFLA as well as of HYPE are hard coded within one script. HYPE version 5.8.0 was used without modifications of the code. At the end of each simulation, HYPE opens a window and asks for a confirmation to exit this window. We have used an auto-clicker to overcome that step. However, modifying the HYPE code would be a better solution for future releases.

Data and Resources

Cite this as

Prajna Kasargodu Anebagilu, Xinyu Li (2022). Dataset: Parameter Optimization for the HYPE model with Shuffled Frog Leaping Algorithm (SFLA). https://doi.org/10.25835/u0wna7hm

DOI retrieved: April 27, 2022

Additional Info

Field Value
Imported on January 12, 2023
Last update January 12, 2023
License CC-BY-3.0
Source https://data.uni-hannover.de/dataset/parameter-optimization-for-the-hype-model-with-shuffled-frog-leaping-algorithm-sfla
Version 0.8
Author Prajna Kasargodu Anebagilu, Xinyu Li
Author Email Prajna Kasargodu Anebagilu, Xinyu Li
Maintainer Jörg Dietrich
Maintainer Email Jörg Dietrich
Source Creation 27 April, 2022, 19:27 PM (UTC+0000)
Source Modified 28 April, 2022, 09:36 AM (UTC+0000)