Fault detection and classification in hybrid energy-based multi-area grid-connected microgrid clusters using discrete wavelet transform with deep neural networks by S. N. V. Bramareswara Rao (21768302)

“…With this intent, this work proposes a “Discrete Wavelet Transform with Deep Neural Network (DWT-DNN)” for detecting and classifying the various faults that occurred in hybrid energy-based multi-area grid-connected microgrid clusters. …”

Multi-Objective Co-optimization of Power and Gas under Uncertainties with P2H embedded by Abdallah, Rawan Yousef Ali

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Privacy-preserving energy optimization via multi-stage federated learning for micro-moment recommendations by Md Mosarrof Hossen (21399056)

A Bayesian Deep Learning Approach With Convolutional Feature Engineering to Discriminate Cyber-Physical Intrusions in Smart Grid Systems by Devinder Kaur (264278)

Reputation-based cooperative detection model of selfish nodes in cluster-based QoS-OLSR protocol. (c2014) by Moati, Nadia

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Exposure of Botnets in Cloud Environment by Expending Trust Model with CANFES Classification Approach by Nagendra Prabhu Selvaraj (17542041)

“…The purpose of this study was to create a multi-layered architecture that could detect a variety of existing and emerging botnets. …”

Building power consumption datasets: Survey, taxonomy and future directions by Yassine Himeur (14158821)

“…Based on the analytical study, a novel dataset has been presented, namely Qatar university dataset, which is an annotated power consumption anomaly detection dataset. The latter will be very useful for testing and training anomaly detection algorithms, and hence reducing wasted energy. …”