Results 211 to 220 of about 766,232 (282)
Numerical simulation of a nonlinear hepatitis B virus mathematical model using the Dickson collocation technique. [PDF]
El-Shenawy A, El-Gamel M, Abouelsaid M.
europepmc +1 more source
Trust‐region filter algorithms utilizing Hessian information for gray‐box optimization
Abstract Optimizing industrial processes often involves gray‐box models that couple algebraic glass‐box equations with black‐box components lacking analytic derivatives. Such systems challenge derivative‐based solvers. The classical trust‐region filter (TRF) algorithm provides a robust framework but requires extensive parameter tuning and numerous ...
Gul Hameed +4 more
wiley +1 more source
Polynomial-time quantum Gibbs sampling for the weak and strong coupling regime of the Fermi-Hubbard model at any temperature. [PDF]
Šmíd Š +3 more
europepmc +1 more source
A trust‐region funnel algorithm for gray‐box optimization
Abstract Gray‐box optimization, where parts of optimization problems are represented by algebraic models while others are treated as black‐box models lacking analytic derivatives, remains a challenge. Trust‐region (TR) methods provide a robust framework for gray‐box problems through local reduced models (RMs) for black‐box components, but they are ...
Gul Hameed +4 more
wiley +1 more source
Full-cycle prediction of crack healing in self-healing concrete using generalized polynomial chaos expansion. [PDF]
Fu C +6 more
europepmc +1 more source
Abstract This article demonstrates the integration of in‐line mass spectrometry as a process analytical technology (PAT) tool with model‐based soft sensors in a continuous filtration‐drying carousel system for solid–liquid separation (SLS) of crystal slurries.
Inyoung Hur +3 more
wiley +1 more source
Performance Analysis and Coefficient Generation Method of Parallel Hammerstein Model Under Underdetermined Condition. [PDF]
Hu N, Xiang Y, Li M, Li X, Tian J.
europepmc +1 more source
AI in chemical engineering: From promise to practice
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 +4 more
wiley +1 more source

