A wind speed forecasting system for the construction of a smart grid with two-stage data processing based on improved ELM and deep learning strategies
The operation and scheduling management of smart grids are important aspects, and wind
speed forecasting modules are indispensable in wind power system management …
speed forecasting modules are indispensable in wind power system management …
Carbon emission prediction models: A review
Y Jin, A Sharifi, Z Li, S Chen, S Zeng, S Zhao - Science of the Total …, 2024 - Elsevier
Amidst growing concerns over the greenhouse effect, especially its consequential impacts,
establishing effective Carbon Emission Prediction Models (CEPMs) to comprehend and …
establishing effective Carbon Emission Prediction Models (CEPMs) to comprehend and …
[HTML][HTML] A fundamental diagram based hybrid framework for traffic flow estimation and prediction by combining a Markovian model with deep learning
Accurate traffic congestion estimation and prediction are critical building blocks for smart trip
planning and rerouting decisions in transportation systems. Over the decades, there have …
planning and rerouting decisions in transportation systems. Over the decades, there have …
A wind speed forecasting method based on EMD-MGM with switching QR loss function and novel subsequence superposition
The ultra-short-term forecasting of wind speed is of great significance to the stable power
supply of the power system. Current wind speed forecasting methods aim to improve …
supply of the power system. Current wind speed forecasting methods aim to improve …
An innovative interpretable combined learning model for wind speed forecasting
P Du, D Yang, Y Li, J Wang - Applied Energy, 2024 - Elsevier
Wind energy is taken as one of the most potential green energy sources, whose accurate
and stable prediction is important to improve the efficiency of wind turbines as well as to …
and stable prediction is important to improve the efficiency of wind turbines as well as to …
A two-stage model for stock price prediction based on variational mode decomposition and ensemble machine learning method
J Zhang, X Chen - Soft Computing, 2024 - Springer
Accurate stock price prediction is critical for investment decisions in the stock market. To
improve the performance of stock price prediction, this paper proposes a novel two-stage …
improve the performance of stock price prediction, this paper proposes a novel two-stage …
Spatial correlation learning based on graph neural network for medium-term wind power forecasting
B Zhao, X He, S Ran, Y Zhang, C Cheng - Energy, 2024 - Elsevier
With the increasing penetration of wind power in power grid, accurate and reliable wind
power forecasting is of great significance for the economic operation and safe dispatching of …
power forecasting is of great significance for the economic operation and safe dispatching of …
Short-term wind farm cluster power prediction based on dual feature extraction and quadratic decomposition aggregation
Z Qu, X Hou, J Li, W Hu - Energy, 2024 - Elsevier
The intermittency and uncertainty of wind energy affect the accuracy of wind power
prediction, which is not conducive to the safe and stable operation of the power system …
prediction, which is not conducive to the safe and stable operation of the power system …
A novel deep-learning framework for short-term prediction of cooling load in public buildings
C Song, H Yang, XB Meng, P Yang, J Cai… - Journal of Cleaner …, 2024 - Elsevier
Optimal control of heating, ventilation, and air conditioning (HVAC) systems, along with
demand-side management, are both cost-effective methods in the process of energy …
demand-side management, are both cost-effective methods in the process of energy …
Estimating fossil CO2 emissions from COVID-19 post-pandemic recovery in G20: A machine learning approach
With the Group of 20 (G20) incorporating climate actions into recovery plans, the post-
COVID period presents a unique opportunity for green economy. Nevertheless, reporting on …
COVID period presents a unique opportunity for green economy. Nevertheless, reporting on …