[HTML][HTML] A taxonomy of machine learning applications for virtual power plants and home/building energy management systems
A Virtual power plant is defined as an information and communications technology system
with the following primary functionalities: enhancing renewable power generation …
with the following primary functionalities: enhancing renewable power generation …
Convolutional neural networks: A survey
M Krichen - Computers, 2023 - mdpi.com
Artificial intelligence (AI) has become a cornerstone of modern technology, revolutionizing
industries from healthcare to finance. Convolutional neural networks (CNNs) are a subset of …
industries from healthcare to finance. Convolutional neural networks (CNNs) are a subset of …
Multivariate Time-Series Forecasting: A Review of Deep Learning Methods in Internet of Things Applications to Smart Cities
V Papastefanopoulos, P Linardatos… - Smart Cities, 2023 - mdpi.com
Smart cities are urban areas that utilize digital solutions to enhance the efficiency of
conventional networks and services for sustainable growth, optimized resource …
conventional networks and services for sustainable growth, optimized resource …
Streamflow prediction using an integrated methodology based on convolutional neural network and long short-term memory networks
Streamflow (Q flow) prediction is one of the essential steps for the reliable and robust water
resources planning and management. It is highly vital for hydropower operation, agricultural …
resources planning and management. It is highly vital for hydropower operation, agricultural …
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 …
Hourly forecasting of solar irradiance based on CEEMDAN and multi-strategy CNN-LSTM neural networks
Accurate and reliable solar irradiance forecasting can bring significant benefits for managing
electricity generation and distributing modern smart grid. However, the characteristics of …
electricity generation and distributing modern smart grid. However, the characteristics of …
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 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 …
[HTML][HTML] Prediction of home energy consumption based on gradient boosting regression tree
P Nie, M Roccotelli, MP Fanti, Z Ming, Z Li - Energy Reports, 2021 - Elsevier
Energy consumption prediction of buildings has drawn attention in the related literature
since it is very complex and affected by various factors. Hence, a challenging work is …
since it is very complex and affected by various factors. Hence, a challenging work is …
Short-term load forecasting using neural networks and global climate models: An application to a large-scale electrical power system
LBS Morais, G Aquila, VAD de Faria, LMM Lima… - Applied Energy, 2023 - Elsevier
This paper focuses on the development of shallow and deep neural networks in the form of
multi-layer perceptron, long-short term memory, and gated recurrent unit to model the short …
multi-layer perceptron, long-short term memory, and gated recurrent unit to model the short …