Review of low voltage load forecasting: Methods, applications, and recommendations
The increased digitalisation and monitoring of the energy system opens up numerous
opportunities to decarbonise the energy system. Applications on low voltage, local networks …
opportunities to decarbonise the energy system. Applications on low voltage, local networks …
Electrical load forecasting models for different generation modalities: a review
The intelligent management of power in electrical utilities depends on the high significance
of load forecasting models. Since the industries are digitalized, power generation is …
of load forecasting models. Since the industries are digitalized, power generation is …
A novel CNN-GRU-based hybrid approach for short-term residential load forecasting
Electric energy forecasting domain attracts researchers due to its key role in saving energy
resources, where mainstream existing models are based on Gradient Boosting Regression …
resources, where mainstream existing models are based on Gradient Boosting Regression …
Human activity recognition via hybrid deep learning based model
In recent years, Human Activity Recognition (HAR) has become one of the most important
research topics in the domains of health and human-machine interaction. Many Artificial …
research topics in the domains of health and human-machine interaction. Many Artificial …
MLT-DNet: Speech emotion recognition using 1D dilated CNN based on multi-learning trick approach
S Kwon - Expert Systems with Applications, 2021 - Elsevier
Speech is the most dominant source of communication among humans, and it is an efficient
way for human–computer interaction (HCI) to exchange information. Nowadays, speech …
way for human–computer interaction (HCI) to exchange information. Nowadays, speech …
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 …
Towards intelligent building energy management: AI-based framework for power consumption and generation forecasting
Due to global warming and climate changes, buildings including residential and commercial
are significant contributors to energy consumption. To this end, net zero energy building …
are significant contributors to energy consumption. To this end, net zero energy building …
Forecasting building energy consumption: Adaptive long-short term memory neural networks driven by genetic algorithm
The real-world building can be regarded as a comprehensive energy engineering system;
its actual energy consumption depends on complex affecting factors, including various …
its actual energy consumption depends on complex affecting factors, including various …
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 …