Results 171 to 180 of about 585,914 (312)
Disciplined Geodesically Convex Programming [PDF]
arXivConvex programming plays a fundamental role in machine learning, data science, and engineering. Testing convexity structure in nonlinear programs relies on verifying the convexity of objectives and constraints. \citet{grant2006disciplined} introduced a framework, Disciplined Convex Programming (DCP), for automating this verification task for a wide ...
arxiv
Crystal Structure Prediction of Cs–Te with Supervised Machine Learning
Advanced Theory and Simulations, EarlyView.High‐throughput density functional theory calculations combined with machine learning models are employed to predict stable Cs– Te binary crystals. By systematically evaluating various structural descriptors and learning algorithms, the superiority of models based on atomic coordination environments is revealed.
Holger‐Dietrich Saßnick +1 more
wiley +1 more source
Extremal problems in the class of close-to-convex functions [PDF]
, 1966 Bernard Pinchuk
openalex +1 more source
SyMO: A Hybrid Approach for Multi‐Objective Optimization of Crystal Growth Processes
Advanced Theory and Simulations, EarlyView.The hybrid SyMO (Symbolic regression Multi‐objective Optimization) framework combines Computational Fluid Dynamics (CFD), machine learning, and mathematical optimization techniques to investigate the effects of various process parameters, furnace geometries, and radiation shield material properties on key crystal quality metrics in Czochralski silicon (
Milena Petkovic, Natasha Dropka
wiley +1 more source
State of the Art of Low‐Frequency Acoustic Modulation: Intensity Enhancement and Directional Control
Advanced Science, EarlyView.High intensity low‐frequency sound sources hold significant value in many fields. However, their long wavelength, strong penetrability, and tendency to diffract make direction control and intensity enhancement challenging. Acoustic generators and metamaterial‐based acoustic devices still face issues such as low energy efficiency, poor directional ...
Jingsong Xu +13 more
wiley +1 more source
Electrostatically Reinforced Double Network Granular Hydrogels
Advanced Science, EarlyView.Electrostatically reinforced double network granular hydrogels (DNGHs) with cartilage‐like fracture energy are introduced. An empirical model predicts the composition‐dependent fracture energy based on dissipation zone size, contact area, and inter‐particle adhesion energy. Thanks to their granular structure and the inter‐particle attraction, the DNGHs
Tianyu Yuan +3 more
wiley +1 more source
AIChE Journal, Volume 69, Issue 1, January 2023., 2023 Abstract In recent years, the catalyst pellets made of open‐cell metallic foams have been identified as a promising alternative in fixed‐bed reactors. A reliable modeling tool is necessary to investigate the suitability of different foam properties and the shapes of foam pellets.
Ginu R. George +7 more
wiley +1 more source
Some inequalities for starshaped and convex functions [PDF]
, 1969 Richard Barlow +2 more
openalex +1 more source
High‐Fidelity Computational Microscopy via Feature‐Domain Phase Retrieval
Advanced Science, EarlyView.An innovative phase retrieval framework, termed FD‐PR, is uniquely established in the image's feature domain through the feature‐extracted, physical‐driven regression with interfaces for combining physics and image processing constraints. FD‐PR takes advantage of invariance components of an image against presences of model mismatch and uncertainty ...
Shuhe Zhang +4 more
wiley +1 more source
AIChE Journal, Volume 69, Issue 2, February 2023., 2023 Abstract This work develops a model predictive control (MPC) scheme using online learning of recurrent neural network (RNN) models for nonlinear systems switched between multiple operating regions following a prescribed switching schedule. Specifically, an RNN model is initially developed offline to model process dynamics using the historical ...
Cheng Hu, Yuan Cao, Zhe Wu
wiley +1 more source