Deep learning-based method for weather forecasting: A case study in Itoshima
<|reference_start|>Deep learning-based method for weather forecasting: A case study in Itoshima: Accurate weather forecasting is of paramount importance for a wide range of practical applications, drawing substantial scientific and societal interest. However, the intricacies of weather systems pose substantial challenges to accurate predictions. This research introduces a multilayer perceptron model tailored for weather forecasting in Itoshima, Kyushu, Japan. Our meticulously designed architecture demonstrates superior performance compared to existing models, surpassing benchmarks such as Long Short-Term Memory and Recurrent Neural Networks.<|reference_end|>
@article{cheng2024deep,
    title={Deep learning-based method for weather forecasting: A case study in
  Itoshima},
    author={Yuzhong Cheng, Linh Thi Hoai Nguyen, Akinori Ozaki, Ton Viet Ta},
    journal={arXiv preprint arXiv:2403.14918},
    year={2024},
    archivePrefix={arXiv},
    eprint={2403.14918},
    primaryClass={cs.LG}
}