Gradient Boosting Applied to Harmonic Distortion Mitigation
Yasmin Martinez
Ahsanullah University of Science and Technology
Abstract
Climate variability and extreme weather increasingly threaten the reliability of flood forecasting in coastal regions. This study employs gradient boosting to characterise the phenomenon under a range of controlled conditions. Applying the method to 4 real-world sites yielded consistent and reproducible results. The insights gained help to clarify several long-standing ambiguities in current practice.
Keywords:
harmonic distortion mitigationgradient boostingconvolutional neural networkwastewater treatmentedge computingresponse surface methodology
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