Results 61 to 70 of about 33,160 (233)

Parameter Identification in a Probabilistic Setting [PDF]

, 2012
Parameter identification problems are formulated in a probabilistic language, where the randomness reflects the uncertainty about the knowledge of the true values. This setting allows conceptually easily to incorporate new information, e.g.
Alexander Litvinenko, Anna Kučerová, Arsigny, Balakrishnan, Becker, Benth, Blanchard, Bobrowski, Bojana V. Rosić, Boyaval, Cao, Christen, Engl, Evensen, Evensen, Galvis, Galvis, Gamerman, Ghanem, Goldstein, Hackbusch, Hermann G. Matthies, Hida, Holden, Ibrahimbegović, Jan Sýkora, Janson, Jaynes, Kučerová, Kučerová, Kučerová, Kálmán, Li, Luenberger, Ma, Madras, Marzouk, Marzouk, Mathelin, Matthies, Matthies, Matthies, Matthies, Matthies, Nouy, Nouy, Oliver Pajonk, Pajonk, Papoulis, Roman, Rosić, Rosić, Saad, Stuart, Stuart, Tarantola, Wiener, Xiu, Zeng, Zienkiewicz   +59 more
core   +2 more sources

A Unifying Approach to Self‐Organizing Systems Interacting via Conservation Laws

Advanced Intelligent Discovery, EarlyView.
The article develops a unified way to model and analyze self‐organizing systems whose interactions are constrained by conservation laws. It represents physical/biological/engineered networks as graphs and builds projection operators (from incidence/cycle structure) that enforce those constraints and decompose network variables into constrained versus ...
F. Barrows, G. Zhang, S. Anand, Z. Chen, J. Lin, A. Desai, S. Martiniani, F. Caravelli   +7 more
wiley   +1 more source

Tracking Modal Parameters of Structures Online Using Recursive Stochastic Subspace Identification under Ambient Excitations

Buildings
Continuous and autonomous system identification is an alternative to regular inspection during operations, which is essential for structural integrity management (SIM) as well as structural health monitoring (SHM).
Shieh-Kung Huang, Jin-Quan Chen, Yuan-Tao Weng, Jae-Do Kang   +3 more
doaj   +1 more source

AI‐Guided Co‐Optimization of Advanced Field‐Effect Transistors: Bridging Material, Device, and Fabrication Design

Advanced Intelligent Discovery, EarlyView.
This article outlines how artificial intelligence could reshape the design of next‐generation transistors as traditional scaling reaches its limits. It discusses emerging roles of machine learning across materials selection, device modeling, and fabrication processes, and highlights hierarchical reinforcement learning as a promising framework for ...
Shoubhanik Nath, Shauryaraj K. Jilkar, Aditya Udgaonkar, Yu (Joe) Lu, Ali Mesbah   +4 more
wiley   +1 more source

Bayesian Optimisation for the Experimental Sciences: A Practical Guide to Data‐Efficient Optimisation of Laboratory Workflows

Advanced Intelligent Systems, EarlyView.
This study provides an introduction to Bayesian optimisation targeted for experimentalists. It explains core concepts, surrogate modelling, and acquisition strategies, and addresses common real‐world challenges such as noise, constraints, mixed variables, scalability, and automation.
Chuan He, Martin Singull, T. Jesper Jacobsson   +2 more
wiley   +1 more source

Operational Modal Analysis Based on Subspace Algorithm with an Improved Stabilization Diagram Method

Shock and Vibration, 2016
Subspace-based algorithms for operational modal analysis have been extensively studied in the past decades. In the postprocessing of subspace-based algorithms, the stabilization diagram is often used to determine modal parameters.
Shiqiang Qin, Juntao Kang, Qiuping Wang
doaj   +1 more source

Data-Driven Diagnostics of Mechanism and Source of Sustained Oscillations [PDF]

, 2015
Sustained oscillations observed in power systems can damage equipment, degrade the power quality and increase the risks of cascading blackouts. There are several mechanisms that can give rise to oscillations, each requiring different countermeasure to ...
Turitsyn, Konstantin, Wang, Xiaozhe
core   +1 more source

Invariant Measure and Universality of the 2D Yang–Mills Langevin Dynamic

Communications on Pure and Applied Mathematics, EarlyView.
ABSTRACT We prove that the Yang–Mills (YM) measure for the trivial principal bundle over the two‐dimensional torus, with any connected, compact structure group, is invariant for the associated renormalised Langevin dynamic. Our argument relies on a combination of regularity structures, lattice gauge‐fixing and Bourgain's method for invariant measures ...
Ilya Chevyrev, Hao Shen
wiley   +1 more source

SUBSPACE IDENTIFICATION - REDUCING UNCERTAINTY ON THE STOCHASTIC PART

IFAC Proceedings Volumes, 2002
Abstract Subspace identification algorithms are user friendly, numerical fast and stable and they provide a good consistent estimate of the deterministic part of a system. The weak point is the stochastic part. The uncertainty on this part is discussed below and methods to reduce it is derived.
openaire   +4 more sources

Random finite element analysis on ground subsidence caused by tunnel excavation in karst regions with spatial variable soil

Deep Underground Science and Engineering, EarlyView.
This study investigates ground subsidence during tunnel excavation in karst areas, highlighting the combined effects of karst cave proximity, cave size, and soil spatial variability. Findings suggest that shorter cave distances and larger cave sizes increase subsidence variability, and a modified Peck formula is proposed for more accurate subsidence ...
Zhenghong Su, Yong Fu, Miaomiao Sun, Kailin Ding, Ying Zhao   +4 more
wiley   +1 more source