Machine learning and deep learning in energy systems: A review
With population increases and a vital need for energy, energy systems play an important
and decisive role in all of the sectors of society. To accelerate the process and improve the …
and decisive role in all of the sectors of society. To accelerate the process and improve the …
Building energy consumption prediction using multilayer perceptron neural network-assisted models; comparison of different optimization algorithms
Building energy prediction has gained significant attention as a thriving research field owing
to its immense potential in enhancing energy efficiency within building energy management …
to its immense potential in enhancing energy efficiency within building energy management …
A deep learning framework using multi-feature fusion recurrent neural networks for energy consumption forecasting
L Fang, B He - Applied Energy, 2023 - Elsevier
Accurate energy load forecasting can not only provide favorable conditions for ensuring
energy security but also reduce carbon emissions and thereby slow down the process of …
energy security but also reduce carbon emissions and thereby slow down the process of …
Intermittent solar power hybrid forecasting system based on pattern recognition and feature extraction
Y Yu, T Niu, J Wang, H Jiang - Energy Conversion and Management, 2023 - Elsevier
Solar energy, with its abundance and accessibility, occupies an irreplaceable position in the
shift in global energy consumption patterns. The difficulties of managing solar energy on the …
shift in global energy consumption patterns. The difficulties of managing solar energy on the …
Building energy consumption prediction and optimization using different neural network-assisted models; comparison of different networks and optimization algorithms
The consumption of energy in buildings holds considerable importance within the realm of
overall energy usage. This underscores the critical nature of employing efficient strategies …
overall energy usage. This underscores the critical nature of employing efficient strategies …
Vulnerability of sustainable markets to fossil energy shocks
Y Li, X Ren, F Taghizadeh-Hesary - Resources Policy, 2023 - Elsevier
From a market efficiency perspective, this study investigates the performance of sustainable
markets under oil price shocks, including green bonds, clean energy, and carbon futures …
markets under oil price shocks, including green bonds, clean energy, and carbon futures …
Using artificial intelligence to rapidly identify microplastics pollution and predict microplastics environmental behaviors
B Hu, Y Dai, H Zhou, Y Sun, H Yu, Y Dai… - Journal of Hazardous …, 2024 - Elsevier
With the massive release of microplastics (MPs) into the environment, research related to
MPs is advancing rapidly. Effective research methods are necessary to identify the chemical …
MPs is advancing rapidly. Effective research methods are necessary to identify the chemical …
Machine learning-based optimization of catalytic hydrodeoxygenation of biomass pyrolysis oil
X Chen, A Shafizadeh, H Shahbeik, S Rafiee… - Journal of Cleaner …, 2024 - Elsevier
Bio-oil derived from biomass pyrolysis contains various oxygenated compounds,
compromising its quality. Catalytic hydrodeoxygenation (HDO) holds promise for upgrading …
compromising its quality. Catalytic hydrodeoxygenation (HDO) holds promise for upgrading …
Residential water and energy consumption prediction at hourly resolution based on a hybrid machine learning approach
Predicting water and energy consumption at high resolution over a short-term horizon is
critical for water and energy resource management. Water and energy are shown to be …
critical for water and energy resource management. Water and energy are shown to be …
A novel grey Lotka–Volterra model driven by the mechanism of competition and cooperation for energy consumption forecasting
Energy is the foundation for the stable operation and long-term growth of the national
economy. Quantifying the degree of competition and cooperation among different types of …
economy. Quantifying the degree of competition and cooperation among different types of …