Results 71 to 80 of about 59,441 (292)

Polynomial chaos Kalman filter for target tracking applications

IET Radar, Sonar & Navigation, 2023
In this paper, an approximate Gaussian state estimator is developed based on generalised polynomial chaos expansion for target tracking applications. Motivated by the fact that calculating conditional moments in an approximate Gaussian filter involves ...
Kundan Kumar, Ranjeet Kumar Tiwari, Shovan Bhaumik, Paresh Date   +3 more
doaj   +1 more source

On the solution of Zabolotskaya–Khokhlov and Diffusion of Oxygen equations using a Sinc collocation method

Partial Differential Equations in Applied Mathematics, 2021
Recent progress seems to suggest that the use of Sinc collocation method for the numerical treatment of partial differential equations, as a great level of precision and accuracy has been obtained on computational grounds.
Iftikhar Ahmad, Syed Ibrar Hussain, Muhammad Usman, Hira Ilyas   +3 more
doaj   +1 more source

AI in chemical engineering: From promise to practice

AIChE Journal, EarlyView.
Abstract Artificial intelligence (AI) in chemical engineering has moved from promise to practice: physics‐aware (gray‐box) models are gaining traction, reinforcement learning complements model predictive control (MPC), and generative AI powers documentation, digitization, and safety workflows.
Jia Wei Chew, Ronnie Andersson, Thomas Bierweiler, Patrik Ryttestal, Torsten Wik   +4 more
wiley   +1 more source

A collocation meshless method based on local optimal point interpolation

International Journal for Numerical Methods in Engineering, 2003
AbstractThis paper deals with the use of the local optimal point interpolating (LOPI) formula in solving partial differential equations (PDEs) with a collocation method. LOPI is an interpolating formula constructed by localization of optimal point interpolation formulas that reproduces polynomials and verifies the delta Kronecker property.
Zuppa, Carlos, Cardona, Alberto
openaire   +3 more sources

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

Sinc-collocation methods with consistent collocation points for Fredholm integral equations of the second kind

Dolomites Research Notes on Approximation, 2023
Sinc-collocation methods are known to be efficient for Fredholm integral equations of the second kind, even if functions in the equations have endpoint singularity. However, existing methods have the disadvantage of inconsistent collocation points. This inconsistency complicates the implementation of such methods, particularly for large-scale problems.
openaire   +3 more sources

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 point collocation approach to modelling large dissipative silencers [PDF]

Journal of Sound and Vibration, 2005
A numerical matching technique known as point collocation is used to model mathematically large dissipative splitter silencers of a type commonly found in HVAC ducts. Transmission loss predictions obtained using point collocation are compared with exact analytic mode matching predictions in the absence of mean flow.
R. Kirby, J.B. Lawrie
openaire   +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

On the Collocation Method in Constructing a Solution to the Volterra Integral Equation of the Second Kind Using Chebyshev and Legendre Polynomials

Известия Иркутского государственного университета: Серия "Математика"
The paper proposes a matrix implementation of the collocation method for constructing a solution to Volterra integral equations of the second kind using systems of orthogonal Chebyshev polynomials of the first kind and Legendre polynomials. The integrand
O.V. Germider, V. N. Popov
doaj   +1 more source