ZongXR / DCIC2024-Offshore-Wind-Power
本赛题要求选手基于风力海况气象数据、风机性能数据等，针对复杂多变气象和海况条件的深度耦合影响，提出海上风电出力预测模型，提升模型精度以及在工程应用中的可信度，为大规模风电接入下的能源安全可靠运行提供保障。A榜得分0.06490342，排名83；B榜得分0.06745705，排名55
☆17Updated last year
Alternatives and similar repositories for DCIC2024-Offshore-Wind-Power:
Users that are interested in DCIC2024-Offshore-Wind-Power are comparing it to the libraries listed below
- wind_power_forecast☆34Updated 2 years ago
- [KDD CUP 2022] 11th place solution of Spatial-Temporal Graph Neural Network for Wind Power Forecasting in Baidu KDD CUP 2022☆55Updated 2 years ago
- Code for Deep Spatio Temporal Wind Power Forecasting☆45Updated 2 years ago
- for the realization of TDformer in the paper "First De-Trend then Attend: Rethinking Attention for Time-Series Forecasting", thank you ve…☆35Updated last year
- ☆37Updated 8 months ago
- 多变量时序预测transformer☆15Updated 2 years ago
- The code for Biased Temporal Convolution Graph Network for Time Series Forecasting with Missing Values.☆23Updated 6 months ago
- KDDCUP2022 Spatial Dynamic Wind Power Forecasting Paddle Track Sixth Place Solution☆22Updated 2 years ago
- Spatial Dynamic Wind Power Forecasting. This task has practical importance for the utilization of wind energy. Participants are expected …☆14Updated 2 years ago
- Code for the paper Transformer-Modulated Diffusion Models for Probabilistic Multivariate Time Series Forecasting☆18Updated 9 months ago
- 本赛题要求选手基于历史光伏发电数据、天气数据、光伏设备空间相对位置等信息，通过建立适当的模型，对未来一段时间内的光伏发电出力进行预测。A榜使用外部数据得分0.88501103804 排名32，未使用外部数据得分0.88042407737 ；B榜得分0.90467829011…☆28Updated 11 months ago
- Addressing prediction delays in time series forecasting: A continuous GRU Approach with derivative regularization☆28Updated 6 months ago
- a multivariate time series deep spatiotemporal forecasting model with graph neural network (MDST-GNN) is proposed to solve the existing …☆32Updated 2 years ago
- PyTorch implementation for paper "WaveForM: Graph Enhanced Wavelet Learning for Long Sequence Forecasting of Multivariate Time Series" (A…☆42Updated 2 years ago
- Official Code for "How Much Can Time-related Features Enhance Time Series Forecasting?"☆34Updated 2 months ago
- The implementation Code of CrossGNN: Confronting Noisy Multivariate Time Series Via Cross Interaction Refinement☆31Updated last year
- An interpretable probabilistic model for short-term solar power forecasting using natural gradient boosting☆15Updated 3 years ago
- ☆104Updated last year
- Traffic Forecasting using Graph Convolution + LSTM model is a ML model developed during the learning process of GCN. The primary soorce o…☆25Updated 4 years ago
- ☆15Updated 2 years ago
- ☆59Updated 2 years ago
- ☆37Updated 2 years ago
- Code release of paper "MLGN: Multi-Scale Local-Global Feature Learning Network for Long-term Series Forecasting" 💚☆15Updated 9 months ago
- Multivariate Time Series Forecasting with Graph Neural Networks☆13Updated 2 years ago
- ☆13Updated 3 years ago
- KDDCUP2022 WPF Competition☆11Updated 2 years ago
- AQI-prediction using Nested LSTM and wavelet transform (WT) based on Keras.☆12Updated 3 years ago
- Dual Dynamic Spatial-Temporal Graph Convolution Network for Traffic Prediction☆43Updated last year
- Official implement for "WITRAN:Water-wave Information Transmission and Recurrent Acceleration Network for Long-range Time Series Forecast…☆34Updated last year