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Scientific Research Publishing4h
Machine Learning-Based Outlier Detection in Long-Term Climate Data: Evidence from Burkina Faso’s Synoptic Network ()
Isolation Forest detects anomalies by isolating observations. It builds binary trees (called iTrees) by recursively ...
IEEE1d
Voltage Transformer Anomaly Detection Using LSTM Based Autoencoder - IEEE Xplore
In this study, we propose a long short-term memory autoencoder (LSTM-AE) based approach for anomaly identification in multivariate time-series measurement data of PTs. Generally, the LSTM-AE is ...
IEEE6d
Bi-LSTM Autoencoder SCADA based Unsupervised Anomaly Detection in Real Wind Farm Data - IEEE Xplore
Intelligent condition monitoring and anomaly detection approaches have become a crucial key for improving safety and reliability of Renewable Energy Systems (RES). However, many challenges arise when ...
devdiscourse19d
New AI model beats traditional systems in detecting fraudulent credit card transactions | Technology - Devdiscourse
The dataset used was a widely known credit card fraud detection benchmark obtained from Kaggle. It is notoriously imbalanced, with only 0.172% of the transactions being fraudulent. To mitigate this, ...
GitHub25d
TransMamba: Time-Frequency Discriminative Feature Learning for Multivariate Time Series Anomaly Detection - GitHub
TransMamba: Time-Frequency Discriminative Feature Learning for Multivariate Time Series Anomaly Detection This repository contains the official PyTorch implementation of our paper: "TransMamba: ...