Bridging the Gap between Energy Consumption and Distribution through Non-Technical Loss Detection

Keywords

Exploit, Bridging (networking), Energy consumption, Computer science, Work (physics)

References

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• FRAUD DETECTION IN ELECTRIC POWER DISTRIBUTION NETWORKS USING AN ANN -BASED KNOWLEDGE -DISCOVERY PROCESSBreno C. Costa, Bruno. L. A Alberto, Andre M. Portela — 2013
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Cited by

• Electricity Theft Detection in Smart Grid Systems: A CNN-LSTM Based ApproachMd. Nazmul Hasan, Rafia Nishat Toma, Abdullah-Al Nahid — 2019
• Knowledge Embedded Semi-Supervised Deep Learning for Detecting Non-Technical Losses in the Smart GridXiaoquan Lu, Yu Zhou, Zhongdong Wang — 2019
• Electricity Theft Detection Using Deep Bidirectional Recurrent Neural NetworkZhongtao Chen, Meng De, Yufan Zhang — 2020
• Detection of Electricity Theft Behavior Based on Improved Synthetic Minority Oversampling Technique and Random Forest ClassifierZhengwei Qu, Hongwen Li, Yunjing Wang — 2020
• Boosting algorithms in energy research: a systematic reviewHristos Tyralis, Georgia Papacharalampous — 2020
• Detection of Non-Technical Losses Using SOSTLink and Bidirectional Gated Recurrent Unit to Secure Smart MetersHira Gul, Nadeem Javaid, Ibrar Ullah — 2020
• An Iterative Approach based on Explainability to Improve the Learning of Fraud Detection ModelsBernat Coma-Puig, Josep Carmona — 2020
• Non-Technical Losses in Light's Concession AreaLucas Merenfeld, Vanessa Huback, Gabriel Hidd — 2020
• Deep Attention-based Neural Network for Electricity Theft DetectionYufan Zhang, Yugang Ji, Ding Xiao — 2020
• CatBoost for big data: an interdisciplinary reviewJohn Hancock, Taghi M. Khoshgoftaar — 2020
• Knowledge-Based Segmentation to Improve Accuracy and Explainability in Non-Technical Losses DetectionAlbert Calvo, Bernat Coma-Puig, Josep Carmona — 2020
• Data-driven framework for the detection of non-technical losses in distribution gridsJ.A. Domínguez-Jiménez, Arias Rivera, K. Botina — 2020
• Electricity Theft Detection using CNN-GRU and Manta Ray Foraging Optimization AlgorithmNasir Ayub, Khursheed Aurangzeb, Muhammad Awais — 2020
• Non-technical losses: A systematic contemporary article reviewFernando de Souza Savian, Júlio Cezar Mairesse Siluk, Taís Bisognin Garlet — 2021
• A review of non-technical loss attack models and detection methods in the smart gridMaria Gabriel Chuwa, Fei Wang — 2021
• Using GANCNN and ERNET for Detection of Non Technical Losses to Secure Smart GridsNadeem Javaid, Hira Gul, Sobia Baig — 2021
• Gradient boosting and Shapley additive explanations for fraud detection in electricity distribution gridsRicardo Nascimento dos Santos, Sami Yamouni, Beatriz Albiero — 2021
• A Human-in-the-Loop Approach based on Explainability to Improve NTL DetectionBernat Coma-Puig, Josep Carmona — 2020
• A Robust Hybrid Deep Learning Model for Detection of Non-Technical Losses to Secure Smart GridsFaisal Shehzad, Nadeem Javaid, Ahmad Almogren — 2021
• Non-technical losses detection in energy consumption focusing on energy recovery and explainabilityBernat Coma-Puig, Josep Carmona — 2021

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