Results 1 to 10 of about 106 (92)

Model order reduction for optimality systems through empirical gramians

Frontiers in Applied Mathematics and Statistics, 2023
In the present article, optimal control problems for linear parabolic partial differential equations (PDEs) with time-dependent coefficient functions are considered.
Luca Mechelli, Jan Rohleff, Stefan Volkwein   +2 more
doaj   +5 more sources

emgr—The Empirical Gramian Framework [PDF]

Algorithms, 2018
System Gramian matrices are a well-known encoding for properties of input-output systems such as controllability, observability or minimality. These so-called system Gramians were developed in linear system theory for applications such as model order ...
Christian Himpe
doaj   +6 more sources

Model order reduction for gas and energy networks

Journal of Mathematics in Industry, 2021
To counter the volatile nature of renewable energy sources, gas networks take a vital role. But, to ensure fulfillment of contracts under these circumstances, a vast number of possible scenarios, incorporating uncertain supply and demand, has to be ...
Christian Himpe, Sara Grundel, Peter Benner   +2 more
doaj   +1 more source

Recognition of Spatiotemporal Feature Images of Zero‐Sequence Voltage for Single‐Phase High‐Impedance Ground Faults Under Complex Conditions

High Voltage, EarlyView.
ABSTRACT Diagnosing high‐impedance ground faults (HIGFs) in distribution networks is extremely challenging because high transition resistance significantly reduces electrical signal strength and unpredictable initial fault phase angles coupled with asymmetric voltage disturbances often lead to misclassification.
Zhengyang Li, Yijia Cao, Chun Chen, Weiyu Wang, Yansha Li, Jinglu Li   +5 more
wiley   +1 more source

Photovoltaic Power Generation Fault Diagnosis Model Based on Multi‐Source Data Fusion Using Neural Network Algorithms

Engineering Reports, Volume 8, Issue 8, August 2026.
This study introduces a multi‐source data fusion framework for PV fault diagnosis that integrates an adaptive CNN with a collaborative data‐feature layer architecture. The model achieves 99.0% accuracy and 98.8% F1‐score, outperforming traditional methods by over 10% and offering a promising solution for reliable PV system monitoring. ABSTRACT Research
Zheng Li, Lin Wang, Huanghuang Jin, Xiaofan Zheng, Guo Zhang, Beibei Wang   +5 more
wiley   +1 more source

A Cyber‐Physical Digital Twin Framework for State Estimation of Dendrite‐Risk Prediction and Resilient Control in Solid‐State Batteries

Global Challenges, Volume 10, Issue 8, August 2026.
A physics‐guided cyber‐physical digital twin enables real‐time state estimation, dendrite‐risk prediction, cyber‐attack detection, and resilient control of solid‐state batteries. Physics‐informed modeling and predictive control reveal hidden degradation mechanisms, providing an interpretable framework for safer, more reliable, and intelligent battery ...
Sankar Subramanian, Prabhu Paulraj, Radhika Subramanian, Lakshmi Narayanan V, Hariprasad Perumal, Mustufa Haider Abidi, Hisham Alkhalefah, Jaber E. Abu Qudeiri, Sachin Salunkhe   +8 more
wiley   +1 more source

Toward a Mixed‐Precision ADI Method for Lyapunov Equations

Proceedings in Applied Mathematics and Mechanics, Volume 26, Issue 2, June 2026.
ABSTRACT We apply mixed‐precision to the low‐rank Lyapunov ADI (LR‐ADI) by performing certain aspects of the algorithm in a lower working precision. Namely, we accumulate the overall solution, solve the linear systems comprising the ADI iteration, and store the inner low‐rank factors of the residuals in various combinations of IEEE 754 single and ...
Jonas Schulze, Jens Saak
wiley   +1 more source

A Sequence‐to‐Sequence Approach for Short‐Term Temperature Prediction With Data Decomposition and Reconstruction

Natural Resource Modeling, Volume 39, Issue 2, May 2026.
ABSTRACT Temperature is an important factor affecting daily life, and accurate multi‐step temperature prediction can provide essential support for weather prediction, energy management, agricultural planning, and disaster mitigation. However, as the prediction horizon extends, the nonlinear nature of temperature data becomes more prominent, making it ...
Baohe Liu, Jing Sha, Ruonan Liu, Lu Wang, Wenjuan Lian   +4 more
wiley   +1 more source

Attenuated Bacteria‐Based Tumor Therapy: Clinical Application Risks, Marketing Approval Restrictions, and Coping Strategies

Advanced Science, Volume 13, Issue 16, 18 March 2026.
This review comprehensively overviews attenuated bacteria‐based tumor therapy, highlighting key methodologies and recent progress. It examines strategies for enhancing safety, stabilizing efficacy, optimizing manufacturing, and navigating regulatory pathways.
Yucheng Liu, Junhong Yao, Jiaxin Deng, Minjie Zhou, Kaiyue Shen, Shishuo Sun, Xiaoge Gao, Qing Zhang, Haiheng Xu   +8 more
wiley   +1 more source

Variable selection via thresholding

Scandinavian Journal of Statistics, Volume 53, Issue 1, Page 207-237, March 2026.
Abstract Variable selection comprises an important step in many modern statistical inference procedures. In the regression setting, when estimators cannot shrink irrelevant signals to zero, covariates without relationships to the response often manifest small but nonzero regression coefficients.
Ka Long Keith Ho, Hien Duy Nguyen
wiley   +1 more source