This is Teletraan team solution for Baidu KDD Cup 2022, winning 3rd place in 2490 teams. The task is to predict the wind farm's future 48 hours active power for every 10 minutes.
- A single BERT model is made from the tfts library created by myself
- Sliding window to generate more samples
- Only 2 raw features are used, wind speed and direction
- The daily fluctuation is added by post-processing to make the predicted result in line with daily periodicity
- Prepare the tensorflow environment
pip install -r requirements.txt- Download the data from Baidu AI studio, and put it in
./data/raw - Train the model
cd src/train
python nn_train.py- The inference code is located in
./submit. The fileresult.zipcreated in./weights/can be submitted.
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