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Low-carbon urban–rural modern energy systems with energy resilience under climate change and extreme events in China—A state-of-the-art review
Y Zhou - Energy and Buildings, 2024 - Elsevier
Climate-adaptive energy resilience and low-carbon transformation are mainstreams to
combat with climate change uncertainty, rural energy poverty, and urban modern energy …
combat with climate change uncertainty, rural energy poverty, and urban modern energy …
Improved multistep ahead photovoltaic power prediction model based on LSTM and self-attention with weather forecast data
Accurate predictions of photovoltaic power generation (PV power) are essential for the
integration of renewable energy into grids, markets, and building energy management …
integration of renewable energy into grids, markets, and building energy management …
A state-of-the-art review on the utilization of machine learning in nanofluids, solar energy generation, and the prognosis of solar power
In the contemporary data-driven era, the fields of machine learning, deep learning, big data,
statistics, and data science are essential for forecasting outcomes and getting insights from …
statistics, and data science are essential for forecasting outcomes and getting insights from …
Adversarial discriminative domain adaptation for solar radiation prediction: A cross-regional study for zero-label transfer learning in Japan
Deep learning models are increasingly applied in the field of solar radiation prediction.
However, the substantial demand for labeled data limits their rapid application in newly …
However, the substantial demand for labeled data limits their rapid application in newly …
A multihead LSTM technique for prognostic prediction of soil moisture
Prognostic prediction of soil moisture is a critical step in various fields such as geotechnical
engineering, agriculture, geology, hydrology, and climatology. For example, in agricultural …
engineering, agriculture, geology, hydrology, and climatology. For example, in agricultural …
A multi-step ahead global solar radiation prediction method using an attention-based transformer model with an interpretable mechanism
Y Zhou, Y Li, D Wang, Y Liu - International Journal of Hydrogen Energy, 2023 - Elsevier
The conventional multi-step ahead solar radiation prediction method ignores the time-
dependence of a future solar radiation time series. Therefore, according to sequence-to …
dependence of a future solar radiation time series. Therefore, according to sequence-to …
Spatio-temporal interpretable neural network for solar irradiation prediction using transformer
Deep learning models have been increasingly applied in the field of solar radiation
prediction. However, the characteristics of a deep learning black box model restrict its …
prediction. However, the characteristics of a deep learning black box model restrict its …
Model predictive control of a building renewable energy system based on a long short-term hybrid model
Considering solar photovoltaic (PV) usage in building energy systems (BES), energy
systems that combine batteries and solar PV (PVB) have been widely used in buildings …
systems that combine batteries and solar PV (PVB) have been widely used in buildings …
Multi-agent reinforcement learning dealing with hybrid action spaces: A case study for off-grid oriented renewable building energy system
With the application of renewable energy in building energy systems (BES), an increasing
number of power grids require building energy systems coupled to realize off-grid operation …
number of power grids require building energy systems coupled to realize off-grid operation …
Deep learning model for the deformation prediction of concrete dams under multistep and multifeature inputs based on an improved autoformer
K Tian, J Yang, L Cheng - Engineering Applications of Artificial Intelligence, 2024 - Elsevier
The long-term prediction of deformation in concrete dams is a critical requirement for
maintaining their structural integrity over time in practical management scenarios. While …
maintaining their structural integrity over time in practical management scenarios. While …