Development of an Extreme Gradient Boosting Model Integrated With Evolutionary Algorithms for Hourly Water Level Prediction

Development of an Extreme Gradient Boosting Model Integrated With Evolutionary Algorithms for Hourly Water Level Prediction

The establishment of reliable water level prediction models is vital for urban flood control and planning. In this paper, we develop hybrid models (GA-XGBoost and DE-XGBoost) that couple two evolutionary models, a genetic algorithm (GA) and a differential evolution (DE) algorithm, with the extreme g...

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Bibliographic Details
Main Authors: Duc Hai Nguyen, Xuan Hien Le, Jae-Yeong Heo, Deg-Hyo Bae
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Extreme gradient boosting
evolutionary algorithms
water level prediction
tree-based model
urban floods
Online Access:https://ieeexplore.ieee.org/document/9531631/

Internet

https://ieeexplore.ieee.org/document/9531631/

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