Turnitin
降AI改写
早检测系统
早降重系统
Turnitin-UK版
万方检测-期刊版
维普编辑部版
Grammarly检测
Paperpass检测
checkpass检测
PaperYY检测
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 …
Wind power forecasting system with data enhancement and algorithm improvement
Y Zhang, X Kong, J Wang, H Wang, X Cheng - Renewable and Sustainable …, 2024 - Elsevier
Wind power generation has strong volatility. Accurate wind speed forecasting can not only
avoid the waste of power resources, but also facilitate the development of clean energy and …
avoid the waste of power resources, but also facilitate the development of clean energy and …
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 …
Bridge deformation prediction based on SHM data using improved VMD and conditional KDE
J **n, Y Jiang, J Zhou, L Peng, S Liu, Q Tang - Engineering Structures, 2022 - Elsevier
Deformation is a paramount index of bridge health monitoring. Accurate prediction of bridge
deformation is of great significance to evaluate bridge performance. However, owing to the …
deformation is of great significance to evaluate bridge performance. However, owing to the …
Decomposition ensemble model based on variational mode decomposition and long short-term memory for streamflow forecasting
G Zuo, J Luo, N Wang, Y Lian, X He - Journal of Hydrology, 2020 - Elsevier
Reliable and accurate streamflow forecasting is vital for water resource management. Many
streamflow prediction studies have demonstrated the excellent prediction ability of …
streamflow prediction studies have demonstrated the excellent prediction ability of …
A new prediction method based on VMD-PRBF-ARMA-E model considering wind speed characteristic
Y Zhang, Y Zhao, C Kong, B Chen - Energy Conversion and Management, 2020 - Elsevier
With the characteristics of randomness, fluctuation, nonlinearity and uncertainty, wind speed
affects the stability of wind power system. In order to improve the safety and stability of wind …
affects the stability of wind power system. In order to improve the safety and stability of wind …
Quaternion convolutional long short-term memory neural model with an adaptive decomposition method for wind speed forecasting: North aegean islands case …
An accurate prediction of short-term and long-term wind speed is necessary in order to
integrate wind energy into large-scale grid power. However, wind speed presents diverse …
integrate wind energy into large-scale grid power. However, wind speed presents diverse …
A composite framework coupling multiple feature selection, compound prediction models and novel hybrid swarm optimizer-based synchronization optimization …
W Fu, K Wang, J Tan, K Zhang - Energy Conversion and Management, 2020 - Elsevier
Accurate wind speed prediction plays a vital role in power system in terms of rational
dispatching and safe operation. For this purpose, a novel composite framework integrating …
dispatching and safe operation. For this purpose, a novel composite framework integrating …
A Tri-dimensional Equilibrium-based stochastic optimal dispatching model for a novel virtual power plant incorporating carbon Capture, Power-to-Gas and electric …
L Ju, Z Yin, X Lu, S Yang, P Li, R Rao, Z Tan - Applied Energy, 2022 - Elsevier
This study proposes a novel structure of carbon-to-power-based virtual power plant (C2P-
VPP) considering the flexible demand response and electric vehicle-to-grid aggregators …
VPP) considering the flexible demand response and electric vehicle-to-grid aggregators …
Sparse Gaussian process regression for multi-step ahead forecasting of wind gusts combining numerical weather predictions and on-site measurements
Accurate forecasts of wind gusts are crucially important for wind power generation, severe
weather warnings, and the regulation of vehicle speed. To improve the short-term and long …
weather warnings, and the regulation of vehicle speed. To improve the short-term and long …