Corpus ID: 218870021

Short-term Load Forecasting Based on Hybrid Strategy Using Warm-start Gradient Tree Boosting

@article{Zhang2020ShorttermLF,
  title={Short-term Load Forecasting Based on Hybrid Strategy Using Warm-start Gradient Tree Boosting},
  author={Yuexin Zhang and J. Wang and S. S. Ge and L. Wang},
  journal={ArXiv},
  year={2020},
  volume={abs/2005.11478}
}
  • Yuexin Zhang, J. Wang, +1 author L. Wang
  • Published 2020
  • Mathematics, Computer Science, Engineering
  • ArXiv
  • A deep-learning based hybrid strategy for short-term load forecasting is presented. The strategy proposes a novel tree-based ensemble method Warm-start Gradient Tree Boosting (WGTB). Current strategies either ensemble submodels of a single type, which fail to take advantage of statistical strengths of different inference models. Or they simply sum the outputs from completely different inference models, which doesn't maximize the potential of ensemble. WGTB is thus proposed and tailored to the… CONTINUE READING

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