Enhancing energy savings verification in industrial settings using deep learning and anomaly detection within the IPMVP framework
This study advances industrial energy Measurement and Verification (M&V) practices by
integrating Deep Learning (DL) techniques with automated anomaly detection, challenging …
integrating Deep Learning (DL) techniques with automated anomaly detection, challenging …
A Data Mining-Based Dynamical Anomaly Detection Method for Integrating with an Advance Metering System
S Maitra - arXiv preprint arXiv:2405.02574, 2024 - arxiv.org
Building operations consume 30% of total power consumption and contribute 26% of global
power-related emissions. Therefore, monitoring, and early detection of anomalies at the …
power-related emissions. Therefore, monitoring, and early detection of anomalies at the …
A Real-time Anomaly Detection Using Convolutional Autoencoder with Dynamic Threshold
S Maitra, S Kundu, A Shankar - arXiv preprint arXiv:2404.04311, 2024 - arxiv.org
The majority of modern consumer-level energy is generated by real-time smart metering
systems. These frequently contain anomalies, which prevent reliable estimates of the series' …
systems. These frequently contain anomalies, which prevent reliable estimates of the series' …
Navigating BIST100 investments through symbolic aggregateapproximation clustering: Insights for investors/Sembolik toplam yaklaşım kümelemesi yoluyla BIST100 …
ME Nalici - 2024 - acikerisim.agu.edu.tr
Market stakeholders, including traders and investors, strive to forecast stock market returns
for informed decision-making. Computational finance employs various tools such as …
for informed decision-making. Computational finance employs various tools such as …
Residual Attention Based TransBiLSTM for Anomaly Electricity Consumption Detection
X Yang, T Han, L Dong, D An - Frontier Academic Forum of Electrical …, 2025 - Springer
Traditional deep learning-based approaches struggle to effectively address long-distance
sequence dependencies in anomaly electricity consumption detection. Hence, we …
sequence dependencies in anomaly electricity consumption detection. Hence, we …
for Anomaly Electricity Consumption Detection
X Yang, T Han, L Dong, D An - The Proceedings of the 11th Frontier … - books.google.com
Traditional deep learning-based approaches struggle to effectively address long-distance
sequence dependencies in anomaly electricity consumption detection. Hence, we …
sequence dependencies in anomaly electricity consumption detection. Hence, we …
Improving Distance Learning Security using Machine Learning
A Ahmad - Journal of Computer Science Application and …, 2023 - journal.lenterailmu.com
This study explores the intersection of machine learning and distance learning security,
aiming to fortify online educational platforms amidst the evolving digital landscape. With …
aiming to fortify online educational platforms amidst the evolving digital landscape. With …