Alternatives and similar repositories for electricity-theft-detection-with-self-attention

Users that are interested in electricity-theft-detection-with-self-attention are comparing it to the libraries listed below

• AbnerYang / TII_Wide-Deep_Electricity_Theft_Detection
  This is the source code of our paper on electricity-theft detection published in TII in the 2017 year.
  ☆36Updated 5 years ago
• henryRDlab / ElectricityTheftDetection
  Electricity-Theft Detection in Smart Grids
  ☆93Updated 6 years ago
• zulfiqarahmadkhan / Electricity-Load-Prediction-Using-CNN-LSTM-autoencoder
  ☆13Updated 4 years ago
• zjunet / HEBR
  Hierarchical Electricity-theft Behavior Recognition
  ☆21Updated 5 years ago
• manastahir / Short-Term-Load-Forecasting
  code for the paper https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9467267
  ☆28Updated 3 years ago
• EsmeYi / time-series-forcasting
  Using K-NN, SVM, Bayes, LSTM, and multi-variable LSTM models on time series forecasting
  ☆49Updated 5 years ago
• flaviagiammarino / deep-tcn-tensorflow
  TensorFlow implementation of DeepTCN model for probabilistic time series forecasting with temporal convolutional networks.
  ☆40Updated last year
• pyae-pyae-phyo / Short-term-electricity-load-forecasting-using-long-short-term-memory
  ☆17Updated 6 years ago
• yunfei1218 / LSTM-Attention
  使用LSTM预测回归问题，使用注意力机制自动提取特征的重要程度。Using LSTM to predict regression problems, Attention mechanism is used to automatically extract the impor…
  ☆18Updated 4 years ago
• YuanSiping / Short-Term-Load-Forecasting-for-Electric-Power-Systems
  ☆63Updated 3 years ago
• kushwahavishal646 / Load-Forecasting-using-Different-Deep-Learning-Architectures
  this project is to implement different deep learning architectures and evaluate them based on their performance on the hour-ahead electri…
  ☆26Updated 4 years ago
• oubahe / TPA-LSTM
  Temporal Pattern Attention for Multivariate Time Series Forecasting
  ☆16Updated 4 years ago
• Varat7v2 / STLF-BiLSTM-CNNBiLSTM
  Short-Term Aggregated Residential Load Forecasting using BiLSTM and CNN-BiLSTM
  ☆33Updated 2 years ago
• joongminpark / Forecasting-TCN
  TCN(Temporal Convolutional Network) model for load forecasting with serial data.
  ☆12Updated 4 years ago
• xbfu / Spatiotemporal-Attention-Networks
  Spatiotemporal Attention Networks for Wind Power Forecasting
  ☆75Updated 5 years ago
• sarikayamehmet / cnn-bilstm-attention
  Multivariate Time Series Prediction using Keras (CNN BiLSTM Attention)
  ☆91Updated 4 years ago
• rqi7 / Unsupervised_Electricity_Theft_Detection
  A Novel Unsupervised Data-Driven Method for Electricity Theft Detection in AMI Using Observer Meters
  ☆14Updated last year
• xiaoguozhi / paper_code
  本人论文实验的一些python与R的代码；《A deep learning based model for short-term power load and probability density forecasting》；《A clustering-based fram…
  ☆18Updated 7 years ago
• getBolted / LoadPredicting
  ARIMA, DBN,FFNN,GBRT,LSTM,RFR,SEQ2SEQ,SVR,XGBOOST
  ☆22Updated 6 years ago
• Om-Prakash08 / Electricity-fraud-detection-using-CNN
  Electricity theft is harmful to power grid suppliers and causes economic losses. Integrating information flows with energy flows, smart g…
  ☆14Updated 3 years ago
• jsyoon0823 / Time-series-prediction
  Basic RNN, LSTM, GRU, and Attention for time-series prediction
  ☆173Updated 7 months ago
• lpphd / multivariate-attention-tcn
  ☆96Updated 2 years ago
• dimitrisbro / SmartGridFraudDetection
  Electricity Fraud Detection in Smart Grids
  ☆9Updated 4 years ago
• oubahe / GSA-PSO-SVR
  一种有效的电力负荷预测方法
  ☆61Updated 5 years ago
• abodh / Electricity-cost-forecasting-using-machine-learning-and-deep-learning-models
  Comparative study of ANN, CNN, LSTM, and ARIMA for time-series forecasting
  ☆21Updated 4 years ago
• UAEUniversity / CIT_LSTM_TimeSeries
  LSTM Model for Electric Load Forecasting
  ☆47Updated 7 years ago
• asurazl / EMD_BiLSTM
  Air Quality Predictions with a Semi-Supervised Bidirectional LSTM Neural Network
  ☆24Updated 3 years ago
• takumiw / Time-Series-Demand-Forecasting
  Time-series demand forecasting is constructed by using LSTM, GRU, LSTM with seq2seq architecture, and prophet models.
  ☆30Updated 4 years ago
• zhangxu0307 / time-series-forecasting-keras
  time series forecasting using keras, inlcuding LSTM,RNN,MLP,GRU,SVR and multi-lag training and forecasting method, ICONIP2017 paper.
  ☆119Updated 6 years ago
• mehak25 / BiGAN
  ☆13Updated 3 years ago