Data-driven prediction and optimization toward net-zero and positive-energy buildings: A systematic review
SN Mousavi, MG Villarreal-Marroquín… - Building and …, 2023 - Elsevier
Recent advances toward sustainable cities have promoted the concept of near-zero energy
consumption. A Positive Energy Building (PEB) model has been developed by the European …
consumption. A Positive Energy Building (PEB) model has been developed by the European …
A comprehensive review on the application of artificial neural networks in building energy analysis
This paper presents a comprehensive review of the significant studies exploited Artificial
Neural Networks (ANNs) in BEA (Building Energy Analysis). To achieve a full coverage of …
Neural Networks (ANNs) in BEA (Building Energy Analysis). To achieve a full coverage of …
Multi-hour and multi-site air quality index forecasting in Beijing using CNN, LSTM, CNN-LSTM, and spatiotemporal clustering
R Yan, J Liao, J Yang, W Sun, M Nong, F Li - Expert Systems with …, 2021 - Elsevier
Effective air quality forecasting models are helpful for timely prevention and control of air
pollution. However, the spatiotemporal distribution characteristics of air quality have not …
pollution. However, the spatiotemporal distribution characteristics of air quality have not …
Rice diseases detection and classification using attention based neural network and bayesian optimization
In this research, an attention-based depthwise separable neural network with Bayesian
optimization (ADSNN-BO) is proposed to detect and classify rice disease from rice leaf …
optimization (ADSNN-BO) is proposed to detect and classify rice disease from rice leaf …
Experimental evaluation of using various renewable energy sources for heating a greenhouse
The interest in alternative or renewable energy sources for greenhouse heating is currently
high, owing to the large heating loads and the relatively high price of fossil fuels. Important …
high, owing to the large heating loads and the relatively high price of fossil fuels. Important …
Temperature prediction of lithium-ion battery based on artificial neural network model
Y Wang, X Chen, C Li, Y Yu, G Zhou, CY Wang… - Applied Thermal …, 2023 - Elsevier
Accurate temperature prediction is one of the most critical problems to improve battery
performance, and prevent thermal runaway. However, the heat generation and heat …
performance, and prevent thermal runaway. However, the heat generation and heat …
Performance of ground heat exchangers: A comprehensive review of recent advances
The importance of investigating and addressing climate change, through the use of
renewable energy, is substantially increasing. Shallow geothermal energy is usually a …
renewable energy, is substantially increasing. Shallow geothermal energy is usually a …
Forecasting cryptocurrency price using convolutional neural networks with weighted and attentive memory channels
After the invention of Bitcoin as well as other blockchain-based peer-to-peer payment
systems, the cryptocurrency market has rapidly gained popularity. Consequently, the …
systems, the cryptocurrency market has rapidly gained popularity. Consequently, the …
Applications of artificial neural networks for thermal analysis of heat exchangers–a review
Artificial neural networks (ANN) have been widely used for thermal analysis of heat
exchangers during the last two decades. In this paper, the applications of ANN for thermal …
exchangers during the last two decades. In this paper, the applications of ANN for thermal …
A review of islanding detection techniques for renewable distributed generation systems
Islanding detection of distributed generations (DGs) is one of the most important aspects of
interconnecting DGs to the distribution system. Islanding detection techniques can generally …
interconnecting DGs to the distribution system. Islanding detection techniques can generally …