A Gradient Boosting Classifier (GBCs)-based detector is used to detect anomalies by considering intentional remedies while non-fraudulent anomaly intervention ...
Oct 14, 2022 · In this paper, a defused decision boundary which renders misclassification issues due to the presence of cross-pairs is investigated.
Oct 9, 2022 · PDF | In this paper, a defused decision boundary which renders misclassification issues due to the presence of cross-pairs is investigated.
In this paper, a defused decision boundary which renders misclassification issues due to the presence of cross-pairs is investigated.
PDF | In this paper, a problem of misclassification due to cross pairs across a decision boundary is investigated. A cross pair is a junction of the two.
In this study, we propose a new hybrid system based on deep learning models that accurately detect electricity theft in smart grids while also being efficient.
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Hence, the present study puts forth a hybrid model that amalgamates a convolutional neural network (CNN) and a transformer network as a means to tackle this ...
... Energy theft detection using gradient boosting theft detector ... Smart Grids Using a Hybrid BiGRU–BiLSTM Model with Feature Engineering-Based Preprocessing.
May 15, 2024 · The key steps of the RoGRUT are data preprocessing that covers the problem of class imbalance, feature extraction and final theft detection.
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How to detect electricity theft?
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Aug 14, 2023 · Data augmentation using BiWGAN, feature extraction and classification by hybrid 2DCNN and BiLSTM to detect non-technical losses in smart grids.