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Enhancing physically-based flood forecasts through fusion of long short-term memory neural network with unscented Kalman filter
Accurate flood forecasts are vital for reservoir operation and flood prevention. The
unscented Kalman filter (UKF) excels in improving physically-based models flood …
unscented Kalman filter (UKF) excels in improving physically-based models flood …
[HTML][HTML] Investigations of Different Approaches for Controlling the Speed of an Electric Motor with Nonlinear Dynamics Powered by a Li-ion Battery–Case Study
RE Tudoroiu, M Zaheeruddin, N Tudoroiu… - Electric vehicles …, 2023 - intechopen.com
This research investigated different nonlinear models, state estimation techniques and
control strategies applied to rechargeable Li-ion batteries and electric motors powered and …
control strategies applied to rechargeable Li-ion batteries and electric motors powered and …
Advancing operational PM2. 5 forecasting with dual deep neural networks (D-DNet)
PM2. 5 forecasting is crucial for public health, air quality management, and policy
development. Traditional physics-based models are computationally demanding and slow to …
development. Traditional physics-based models are computationally demanding and slow to …
Assembly makespan estimation using features extracted by a topic model
Z Hu, Y Cheng, H **ong, X Zhang - Knowledge-Based Systems, 2023 - Elsevier
Accurate makespan estimation is imperative during production scheduling to increase the
flexibility and efficiency of work plans. However, given the complexities of production …
flexibility and efficiency of work plans. However, given the complexities of production …
[HTML][HTML] A Deep U-Net-ConvLSTM Framework with Hydrodynamic Model for Basin-Scale Hydrodynamic Prediction
A Li, W Zhang, X Zhang, G Chen, X Liu, A Jiang… - Water, 2024 - mdpi.com
Traditional hydrodynamic models face the significant challenge of balancing the demands of
long prediction spans and precise boundary conditions, large computational areas, and low …
long prediction spans and precise boundary conditions, large computational areas, and low …
Ensemble Multitask Prediction of Air Pollutants Time Series: Based on Variational Inference, Data Projection, and Generative Adversarial Network
K Wang, C Qu, J Wang, Z Li, H Lu - Journal of Forecasting, 2024 - Wiley Online Library
In light of the mounting environmental pressures, especially the significant threat urban air
pollution poses to public health, there arises an imperative need to develop a data‐driven …
pollution poses to public health, there arises an imperative need to develop a data‐driven …
Beyond conventional predictions: unfolding the ensemble Kalman filter's publications in renewable energy
K Obaideen, Y Faroukh… - Energy Harvesting and …, 2024 - spiedigitallibrary.org
Within the process of development of sustainable energy solutions, the Ensemble Kalman
Filter (EnKF) holds an allimportant key by assisting in forecasting and optimization of …
Filter (EnKF) holds an allimportant key by assisting in forecasting and optimization of …
Analysis of the extended Kalman filter's role in oceanic science
This study delves into the Extended Kalman Filter's (EKF) use in ocean science through a
detailed bibliometric and text mining examination. Tracing its roots back to the original …
detailed bibliometric and text mining examination. Tracing its roots back to the original …