Results 121 to 130 of about 21,185 (243)
To address high‐altitude power transmission challenges, a composite controller was developed to suppress strong wind interference, demonstrating the effectiveness of hierarchical control in complex dynamic systems. Hardware‐in‐the‐loop experiments verified the robustness of the control algorithm, providing methodological support for developing ...
Shaofeng Bai, Jun Zhong
wiley +1 more source
Entropy-Guided Regime Switching for Railway Passenger Flow Forecasting: An Adaptive EA-ARIMA-Informer Framework. [PDF]
Tan S, Shan X, Wei Z, Zhao S, Wu J.
europepmc +1 more source
ABSTRACT This study compares parametric statistical time series models, such as autoregressive moving average (ARMA), with nonparametric artificial neural networks, specifically long short‐term memory (LSTM) models, for univariate forecasting. Two time series are analyzed separately: wind power output from the Clements Gap wind farm and the regional ...
Luigi R. Cirocco +3 more
wiley +1 more source
Real-time dynamic prediction of HFMD transmission using SEIRQ-ARIMA hybrid model optimized by multi-stage ABC-GWO algorithm. [PDF]
Zeng Z, Sathasivam S, Xin J, Zhao H.
europepmc +1 more source
American Journal of Hematology, Volume 101, Issue 3, Page 577-580, March 2026.
Marina Konopleva +8 more
wiley +1 more source
Forecasting Carbon Prices: A Literature Review
ABSTRACT Carbon emissions trading is utilized by a growing number of states as a significant tool for addressing greenhouse gas emissions (GHG), global warming problem and the climate crisis. Accurate forecasting of carbon prices is essential for effective policy design and investment strategies in climate change mitigation.
Konstantinos Bisiotis +2 more
wiley +1 more source
Forecasting Road Traffic Injuries in North-Eastern Iran: The Effects of COVID-19 and Time Series Analysis (2009-2023). [PDF]
Akbari Khalaj T +6 more
europepmc +1 more source
A Novel Approach to Forecasting After Large Forecast Errors
ABSTRACT A sequence of increasingly large same‐sign 1‐step‐ahead forecast errors are most likely due to a sudden unexpected shift. Large forecast errors can be expensive, but also contain valuable information. Impulse indicators acting as intercept corrections to set forecasts back on track can be quickly tested for replacing outliers, a location shift
Jennifer L. Castle +2 more
wiley +1 more source
Infectious disease prediction model based on optimized deep learning algorithm. [PDF]
Cao Q +7 more
europepmc +1 more source

