Results 41 to 50 of about 720 (191)

Numerical Analysis of a Transmission Line Illuminated by a Random Plane-Wave Field Using Stochastic Reduced Order Models

IEEE Access, 2017
A novel nonintrusive statistical approach, known as the stochastic reduced order model (SROM) method, is applied to efficiently estimate the statistical information of the terminal response (i.e., the induced current) in transmission lines excited by a ...
Zhouxiang Fei, Yi Huang, Jiafeng Zhou, Chaoyun Song   +3 more
doaj   +1 more source

CrossMatAgent: AI‐Assisted Design of Manufacturable Metamaterial Patterns via Multi‐Agent Generative Framework

Advanced Intelligent Discovery, EarlyView.
CrossMatAgent is a multi‐agent framework that combines large language models and diffusion‐based generative AI to automate metamaterial design. By coordinating task‐specific agents—such as describer, architect, and builder—it transforms user‐provided image prompts into high‐fidelity, printable lattice patterns.
Jie Tian, Martin Taylor Sobczak, Dhanush Patil, Jixin Hou, Lin Pang, Arunachalam Ramanathan, Libin Yang, Xianyan Chen, Yuval Golan, Xiaoming Zhai, Hongyue Sun, Kenan Song, Xianqiao Wang   +12 more
wiley   +1 more source

Stochastic Optimization of Economic Dispatch With Wind and Photovoltaic Energy Using the Nested Sparse Grid-Based Stochastic Collocation Method

IEEE Access, 2019
Due to the increasing uncertainty brought about by renewable energy, conventional deterministic dispatch approaches have not been very applicative. This paper investigates a nested sparse grid-based stochastic collocation method (NS-SCM) as a possible ...
Zhilin Lu, Mingbo Liu, Wentian Lu, Zhuoming Deng   +3 more
doaj   +1 more source

Stochastic Optimal Power Flow for Power Systems Considering Wind Farms Based on the Stochastic Collocation Method

IEEE Access, 2022
The investigation of stochastic optimal power flow (SOPF) is to seek the optimal solution of static stability constrained optimal power flow considering the uncertainty of parameters in power systems. To solve the problem, this paper proposes an approach
Bingqing Xia, Yuwei Chen, Wenbin Yang, Qing Chen, Xiaohe Wang, Kuan Min   +5 more
doaj   +1 more source

Disentangling Aleatoric and Epistemic Uncertainty in Physics‐Informed Neural Networks: Application to Insulation Material Degradation Prognostics

Advanced Intelligent Systems, EarlyView.
Physics‐Informed Neural Networks (PINNs) provide a framework for integrating physical laws with data. However, their application to Prognostics and Health Management (PHM) remains constrained by the limited uncertainty quantification (UQ) capabilities.
Ibai Ramirez, Jokin Alcibar, Joel Pino, Mikel Sanz, Jose I. Aizpurua   +4 more
wiley   +1 more source

Stochastic collocation method for computing eigenspaces of parameter-dependent operators

Numerische Mathematik, 2022
AbstractWe consider computing eigenspaces of an elliptic self-adjoint operator depending on a countable number of parameters in an affine fashion. The eigenspaces of interest are assumed to be isolated in the sense that the corresponding eigenvalues are separated from the rest of the spectrum for all values of the parameters.
Luka Grubisic, Mikael Saarikangas, Harri Hakula   +2 more
openaire   +4 more sources

Probability prediction of true‐triaxial compressive strength of intact rocks based on the improved PSO‐RVM model

Deep Underground Science and Engineering, EarlyView.
In this work, we propose an improved particle swarm optimization (PSO) algorithm and develop an improved PSO‐relevance vector machine (RVM) model as a substitute for traditional true‐triaxial testing. The model's high prediction accuracy was validated through comparisons with two other machine learning methods and five three‐dimensional Hoek–Brown type
Qi Zhang, Maohui Wang, Ning Wang, Yixin Shen, Xuzhen He   +4 more
wiley   +1 more source

Sensitivity analysis to compute advanced stochastic problems in uncertain and complex electromagnetic environments

Advanced Electromagnetics, 2012
This paper deals with the advanced integration of uncertainties in electromagnetic interferences (EMI) and electromagnetic compatibility (EMC) problems.
S. Lalléchère, B. Jannet, P. Bonnet, F. Paladian   +3 more
doaj   +1 more source

Stability Evaluation and Parametric Optimization of Coal‐Concrete Composite Bearing Systems Under Mine‐Water‐Induced Deterioration: Experiments and FEINN Analysis

Energy Science &Engineering, EarlyView.
Mine‐water immersion tests reveal pronounced coal weakening (vs. minor concrete degradation), identifying coal pillars as the stability‐limiting component in composite dams. A coupled FEINN framework quantifies extreme‐pressure stability and ranks multi‐parameter designs via a normalized multi‐indicator scheme, enabling optimized dam configuration for ...
He Wen, Hongchuan Dai, Guixin Zhang, Pengzhe Li, Tong Yang, Cang Gong, Renbo Gao   +6 more
wiley   +1 more source

A test of backward stochastic differential equations solver for solving semilinear parabolic differential equations in 1D and 2D

Partial Differential Equations in Applied Mathematics, 2022
Backward stochastic differential equation solver was first introduced by Han et al in 2017. A semilinear parabolic partial differential equation is converted into a stochastic differential equation, and then solved by the backward stochastic differential
Evan Davis, Guangming Yao, Elizabeth Javor, Kalani Rubasinghe, Luis Antonio Topete Galván   +4 more
doaj   +1 more source