A review of wind speed and wind power forecasting with deep neural networks
The use of wind power, a pollution-free and renewable form of energy, to generate electricity
has attracted increasing attention. However, intermittent electricity generation resulting from …
has attracted increasing attention. However, intermittent electricity generation resulting from …
Drug discovery with explainable artificial intelligence
Deep learning bears promise for drug discovery, including advanced image analysis,
prediction of molecular structure and function, and automated generation of innovative …
prediction of molecular structure and function, and automated generation of innovative …
A review and evaluation of the state-of-the-art in PV solar power forecasting: Techniques and optimization
Integration of photovoltaics into power grids is difficult as solar energy is highly dependent
on climate and geography; often fluctuating erratically. This causes penetrations and voltage …
on climate and geography; often fluctuating erratically. This causes penetrations and voltage …
A review of deep learning for renewable energy forecasting
As renewable energy becomes increasingly popular in the global electric energy grid,
improving the accuracy of renewable energy forecasting is critical to power system planning …
improving the accuracy of renewable energy forecasting is critical to power system planning …
A convolutional Transformer-based truncated Gaussian density network with data denoising for wind speed forecasting
Y Wang, H Xu, M Song, F Zhang, Y Li, S Zhou, L Zhang - Applied Energy, 2023 - Elsevier
Wind speed forecasting plays an important role in the stable operation of wind energy power
systems. However, accurate and reliable wind speed forecasting faces four challenges: how …
systems. However, accurate and reliable wind speed forecasting faces four challenges: how …
Evolutionary quantile regression gated recurrent unit network based on variational mode decomposition, improved whale optimization algorithm for probabilistic short …
C Zhang, C Ji, L Hua, H Ma, MS Nazir, T Peng - Renewable Energy, 2022 - Elsevier
Wind energy, as clean energy, has attracted more and more attention. Wind power
generation is easily threatened by the irregular fluctuation of wind speed, which interferes …
generation is easily threatened by the irregular fluctuation of wind speed, which interferes …
Interval forecasting for urban water demand using PSO optimized KDE distribution and LSTM neural networks
B Du, S Huang, J Guo, H Tang, L Wang, S Zhou - Applied Soft Computing, 2022 - Elsevier
The current literature on water demand forecasting mostly focuses on giving accurate point
predictions of water demand. However, the water demand point forecasting will encounter …
predictions of water demand. However, the water demand point forecasting will encounter …
Review on probabilistic forecasting of photovoltaic power production and electricity consumption
Abstract tAccurate forecasting simultaneously becomes more important and more
challenging due to the increasing penetration of photovoltaic (PV) systems in the built …
challenging due to the increasing penetration of photovoltaic (PV) systems in the built …
High-quality prediction intervals for deep learning: A distribution-free, ensembled approach
This paper considers the generation of prediction intervals (PIs) by neural networks for
quantifying uncertainty in regression tasks. It is axiomatic that high-quality PIs should be as …
quantifying uncertainty in regression tasks. It is axiomatic that high-quality PIs should be as …
Short-term wind speed interval prediction based on ensemble GRU model
Wind speed interval prediction is playing an increasingly important role in wind power
production. The intermittent and fluctuant characteristics of wind power make high-quality …
production. The intermittent and fluctuant characteristics of wind power make high-quality …