Weather-Adaptive Multi-Step Forecasting of State of Polarization Changes in Aerial Fibers Using Wavelet Neural Networks
<|reference_start|>Weather-Adaptive Multi-Step Forecasting of State of Polarization Changes in Aerial Fibers Using Wavelet Neural Networks: We introduce a novel weather-adaptive approach for multi-step forecasting of multi-scale SOP changes in aerial fiber links. By harnessing the discrete wavelet transform and incorporating weather data, our approach improves forecasting accuracy by over 65% in RMSE and 63% in MAPE compared to baselines.<|reference_end|>
@article{abdelli2024weather-adaptive,
    title={Weather-Adaptive Multi-Step Forecasting of State of Polarization Changes
  in Aerial Fibers Using Wavelet Neural Networks},
    author={Khouloud Abdelli, Matteo Lonardi, Jurgen Gripp, Samuel Olsson Fabien
  Boitier, and Patricia Layec},
    journal={arXiv preprint arXiv:2409.03663},
    year={2024},
    archivePrefix={arXiv},
    eprint={2409.03663},
    primaryClass={cs.NI cs.LG}
}