Results 31 to 40 of about 641 (195)

A Novel Method for Solving Second Kind Volterra Integral Equations with Discontinuous Kernel

Mathematics, 2021
Load leveling problems and energy storage systems can be modeled in the form of Volterra integral equations (VIE) with a discontinuous kernel. The Lagrange–collocation method is applied for solving the problem. Proving a theorem, we discuss the precision
Samad Noeiaghdam, Sanda Micula
doaj   +1 more source

Density estimation for time-dependent PDE with random input by a Legendre-based multi-element probabilistic collocation method

AIP Advances
This paper proposed a Legendre-based multi-element probabilistic collocation method for time-dependent stochastic differential equations, used for density estimation of unknown functions.
Hongling Xie
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

Radiation Transport in Random Media With Large Fluctuations

EPJ Web of Conferences, 2017
Neutral particle transport in media exhibiting large and complex material property spatial variation is modeled by representing cross sections as lognormal random functions of space and generated through a nonlinear memory-less transformation of a ...
Olson Aaron, Prinja Anil, Franke Brian
doaj   +1 more source

RAMS: Residual‐Based Adversarial‐Gradient Moving Sample Method for Scientific Machine Learning in Solving Partial Differential Equations

Advanced Intelligent Discovery, EarlyView.
We propose a residual‐based adversarial‐gradient moving sample (RAMS) method for scientific machine learning that treats samples as trainable variables and updates them to maximize the physics residual, thereby effectively concentrating samples in inadequately learned regions.
Weihang Ouyang, Min Zhu, Wei Xiong, Si‐Wei Liu, Lu Lu   +4 more
wiley   +1 more source

A mixed-method to numerical simulation of variable order stochastic advection diffusion equations

Alexandria Engineering Journal
The study of stochastic problems is very important and there is an increasing demand for investigating the behavior of a number of sophisticated dynamical systems in different areas of science as well as in engineering and finance.
H. Jafari, R.M. Ganji, S. Salati, S.J. Johnston   +3 more
doaj   +1 more source

Parametric Transient Stability Constrained Optimal Power Flow Solved by Polynomial Approximation Based on the Stochastic Collocation Method

Energies, 2022
To better respond to the impact of power system-uncertain parameters on transient stability, a novel model named the parametric transient stability constrained optimal power flow (parametric TSCOPF) is proposed.
Bingqing Xia, Hao Wu, Wenbin Yang, Lu Cao, Yonghua Song   +4 more
doaj   +1 more source

VAE+DDPG: An Attention‐Enhanced Variational Autoencoder for Deep Reinforcement Learning‐Based Autonomous Navigation in Low‐Light Environments

Advanced Intelligent Systems, EarlyView.
Variational Autoencoder+Deep Deterministic Policy Gradient addresses low‐light failures of infrared depth sensing for indoor robot navigation. Stage 1 pretrains an attention‐enhanced Variational Autoencoder (Convolutional Block Attention Module+Feature Pyramid Network) to map dark depth frames to a well‐lit reconstruction, yielding a 128‐D latent code ...
Uiseok Lee, Chanhong Hwang, Hyunseok Kang, Yechan Park, Hangwoo Jin, Tuan Anh Nguyen, Eunmi Choi, Dugki Min   +7 more
wiley   +1 more source

Efficient Solutions for Stochastic Fractional Differential Equations with a Neutral Delay Using Jacobi Poly-Fractonomials

Mathematics
This paper introduces a novel numerical technique for solving fractional stochastic differential equations with neutral delays. The method employs a stepwise collocation scheme with Jacobi poly-fractonomials to consider unknown stochastic processes.
Afshin Babaei, Sedigheh Banihashemi, Behrouz Parsa Moghaddam, Arman Dabiri, Alexandra Galhano   +4 more
doaj   +1 more source

Review of Memristors for In‐Memory Computing and Spiking Neural Networks

Advanced Intelligent Systems, EarlyView.
Memristors uniquely enable energy‐efficient, brain‐inspired computing by acting as both memory and synaptic elements. This review highlights their physical mechanisms, integration in crossbar arrays, and role in spiking neural networks. Key challenges, including variability, relaxation, and stochastic switching, are discussed, alongside emerging ...
Mostafa Shooshtari, Teresa Serrano‐Gotarredona, Bernabé Linares‐Barranco   +2 more
wiley   +1 more source