InfoQ

Fraud Detection Using Random Forest, Neural Autoencoder, and Isolation Forest Techniques

Key Takeaways Fraud detection techniques mostly stem from the anomaly detection branch of data science. If the dataset has sufficient number of fraud examples, supervised machine learning algorithms ...
Devdiscourse

AI for Energy Security: Study Compares LSTM and FFNN in Solar Grid Anomaly Detection

Researchers from Noida International University and Dayananda Sagar University explored deep learning models for anomaly detection in solar power systems, comparing LSTM, FFNN, and Isolation Forest ...
InfoQ

Fraud Detection Using Random Forest, Neural Autoencoder, and Isolation Forest Techniques

A monthly overview of things you need to know as an architect or aspiring architect. Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with ...