{
  "context_length": 336,
  "prediction_length": 48,
  "windows": 6,
  "stride": 24,
  "device": "cpu",
  "datasets": [
    {
      "key": "gefcom_load",
      "title": "GEFCom2014 electricity load",
      "source_url": "https://blog.drhongtao.com/2017/03/gefcom2014-load-forecasting-data.html",
      "download_url": "https://www.dropbox.com/s/pqenrr2mcvl0hk9/GEFCom2014.zip?dl=1",
      "target_name": "Hourly electric load, zone 1",
      "frequency_label": "hourly",
      "horizon_label": "24 steps = 24 hours",
      "covariate_note": "25 weather-station temperature series plus temperature aggregates and calendar encodings."
    },
    {
      "key": "gefcom_solar",
      "title": "GEFCom2014 solar generation",
      "source_url": "https://www.sciencedirect.com/science/article/pii/S0169207016000133",
      "download_url": "https://www.dropbox.com/s/pqenrr2mcvl0hk9/GEFCom2014.zip?dl=1",
      "target_name": "Hourly solar power, zone 1",
      "frequency_label": "hourly",
      "horizon_label": "24 steps = 24 hours",
      "covariate_note": "Numerical weather prediction variables from the solar track plus calendar encodings."
    },
    {
      "key": "ett_transformer",
      "title": "Electricity Transformer Temperature",
      "source_url": "https://github.com/zhouhaoyi/ETDataset",
      "download_url": "https://raw.githubusercontent.com/zhouhaoyi/ETDataset/main/ETT-small/ETTh1.csv",
      "target_name": "Transformer oil temperature",
      "frequency_label": "hourly",
      "horizon_label": "24 steps = 24 hours",
      "covariate_note": "High/medium/low useful and useless load measurements plus calendar encodings."
    }
  ]
}