A simplified LSTM neural networks for one day-ahead solar power forecasting
CH Liu, JC Gu, MT Yang - Ieee Access, 2021 - ieeexplore.ieee.org
In recent years, exploration and exploitation of renewable energies are turning a new
chapter toward the development of energy policy, technology and business ecosystem in all …
chapter toward the development of energy policy, technology and business ecosystem in all …
Short-term prediction of COVID-19 cases using machine learning models
The first case in Bangladesh of the novel coronavirus disease (COVID-19) was reported on
8 March 2020, with the number of confirmed cases rapidly rising to over 175,000 by July …
8 March 2020, with the number of confirmed cases rapidly rising to over 175,000 by July …
Short-term apartment-level load forecasting using a modified neural network with selected auto-regressive features
Residential electricity load profiles and their diversity have become increasingly important to
realize the benefits of Smart or Transactive Energy Networks (TENs). An important element …
realize the benefits of Smart or Transactive Energy Networks (TENs). An important element …
Large-scale comparison and demonstration of continual learning for adaptive data-driven building energy prediction
Data-driven models have been increasingly employed in smart building energy
management. To avoid performance degradation over time, data-driven models need to be …
management. To avoid performance degradation over time, data-driven models need to be …
[HTML][HTML] A predictive maintenance model using long short-term memory neural networks and Bayesian inference
D Pagano - Decision Analytics Journal, 2023 - Elsevier
The fourth industrial revolution is a profound transformation utilizing emerging technologies
like smart automation, large-scale machine-to-machine communication, and the internet of …
like smart automation, large-scale machine-to-machine communication, and the internet of …
Anomaly detection for insider attacks from untrusted intelligent electronic devices in substation automation systems
In recent decades, cyber security issues in IEC 61850-compliant substation automation
systems (SASs) have become growing concerns. Many researchers have developed various …
systems (SASs) have become growing concerns. Many researchers have developed various …
Elastic weight consolidation-based adaptive neural networks for dynamic building energy load prediction modeling
Data-driven building energy load prediction models should be updated dynamically to adapt
to building performance degradation and changes of outdoor environment. Conventional …
to building performance degradation and changes of outdoor environment. Conventional …
Efficient and robust online trajectory prediction for non-cooperative unmanned aerial vehicles
As an important type of dynamic data-driven application system, unmanned aerial vehicles
(UAVs) are widely used for civilian, commercial, and military applications across the globe …
(UAVs) are widely used for civilian, commercial, and military applications across the globe …
[HTML][HTML] Industrial kitchen appliance consumption forecasting: Hour-ahead and day-ahead perspectives with post-processing improvements
Forecasting techniques have gained considerable prominence within the electric energy
sector. Many studies have been documented in the literature, addressing various facets of …
sector. Many studies have been documented in the literature, addressing various facets of …
[PDF][PDF] Human activity recognition with openpose and Long Short-Term Memory on real time images
C Sawant - EasyChair Preprint, 2020 - easychair.org
Abstract—Human Activity Recognition (HAR) is a broad field of study aims to classify time
series activities. These activities can include normal body movements such as standing up …
series activities. These activities can include normal body movements such as standing up …