AI-big data analytics for building automation and management systems: a survey, actual challenges and future perspectives
In theory, building automation and management systems (BAMSs) can provide all the
components and functionalities required for analyzing and operating buildings. However, in …
components and functionalities required for analyzing and operating buildings. However, in …
Machine Learning, Deep Learning and Statistical Analysis for forecasting building energy consumption—A systematic review
The building sector accounts for 36% of the total global energy usage and 40% of
associated Carbon Dioxide emissions. Therefore, the forecasting of building energy …
associated Carbon Dioxide emissions. Therefore, the forecasting of building energy …
Long short-term memory network-based metaheuristic for effective electric energy consumption prediction
SK Hora, R Poongodan, RP De Prado, M Wozniak… - Applied Sciences, 2021 - mdpi.com
The Electric Energy Consumption Prediction (EECP) is a complex and important process in
an intelligent energy management system and its importance has been increasing rapidly …
an intelligent energy management system and its importance has been increasing rapidly …
Dual stream network with attention mechanism for photovoltaic power forecasting
The operations of renewable power generation systems highly depend on precise
Photovoltaic (PV) power forecasting, providing significant economic, and environmental …
Photovoltaic (PV) power forecasting, providing significant economic, and environmental …
Towards smart home automation using IoT-enabled edge-computing paradigm
Smart home applications are ubiquitous and have gained popularity due to the
overwhelming use of Internet of Things (IoT)-based technology. The revolution in …
overwhelming use of Internet of Things (IoT)-based technology. The revolution in …
Efficient short-term electricity load forecasting for effective energy management
Short-term electrical energy load forecasting is one of the most significant problems
associated with energy management for smart grids, which aims to optimize the operational …
associated with energy management for smart grids, which aims to optimize the operational …
DB-Net: A novel dilated CNN based multi-step forecasting model for power consumption in integrated local energy systems
In the era of cutting edge technology, excessive demand for electricity is rising day by day,
due to the exponential growth of population, electricity reliant vehicles, and home …
due to the exponential growth of population, electricity reliant vehicles, and home …
An effective skin cancer classification mechanism via medical vision transformer
Skin Cancer (SC) is considered the deadliest disease in the world, killing thousands of
people every year. Early SC detection can increase the survival rate for patients up to 70 …
people every year. Early SC detection can increase the survival rate for patients up to 70 …
Randomly initialized CNN with densely connected stacked autoencoder for efficient fire detection
Vision sensors-based fire detection is an interesting and useful research domain with
significant alleviated attention from computer vision experts. The baseline research is based …
significant alleviated attention from computer vision experts. The baseline research is based …
[HTML][HTML] Enhancing interpretability in power management: A time-encoded household energy forecasting using hybrid deep learning model
Nowadays, residential households, including both consumers and emerging prosumers,
have exhibited a growing demand for active/reactive power. This demand surge arises from …
have exhibited a growing demand for active/reactive power. This demand surge arises from …