• Corpus ID: 208617482

Predicting Lake Erie Wave Heights using XGBoost

@article{Hu2019PredictingLE,
  title={Predicting Lake Erie Wave Heights using XGBoost},
  author={Haoguo Hu and Philip Chu},
  journal={ArXiv},
  year={2019},
  volume={abs/1912.01786}
}
Dangerous large wave put the coastal communities and vessels operating under threats and wave predictions are strongly needed for early warnings. While numerical wave models, such as WAVEWATCH III (WW3), are useful to provide spatially continuous information to supplement in situ observations, however, they often require intensive computational costs. An attractive alternative is machine-learning method, which can potentially provide comparable performance of numerical wave models but only… 

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