Results 51 to 60 of about 35,631 (308)

An Offline Weighted-Bagging Data-Driven Evolutionary Algorithm with Data Generation Based on Clustering

Mathematics, 2023
In recent years, a variety of data-driven evolutionary algorithms (DDEAs) have been proposed to solve time-consuming and computationally intensive optimization problems.
Zongliang Guo, Sikai Lin, Runze Suo, Xinming Zhang   +3 more
doaj   +1 more source

Multimodal Data‐Driven Microstructure Characterization

Advanced Engineering Materials, EarlyView.
A self‐consistent autonomous workflow for EBSP‐based microstructure segmentation by integrating PCA, GMM clustering, and cNMF with information‐theoretic parameter selection, requiring no user input. An optimal ROI size related to characteristic grain size is identified.
Qi Zhang, Santiago Benito, Özge Özgün, Sebastian Weber, Markus Stricker   +4 more
wiley   +1 more source

Filtered-X Radial Basis Function Neural Networks for Active Noise Control [PDF]

ITB Journal of Engineering Science, 2004
This paper presents active control of acoustic noise using radial basis function (RBF) networks and its digital signal processor (DSP) real-time implementation.
Bambang Riyanto, Lazuardi Anggono, Kenko Uchida   +2 more
doaj  

Current Status and Challenges in Data Collection for Aerospace Coatings Deposited by Plasma Spraying

Advanced Engineering Materials, EarlyView.
An innovative approach has been integrated into the GRENAT project to optimize plasma spraying and coating performance. Raw materials are accelerated and melted in the plasma generated by torches, creating coatings. Monitoring sensors collect process data which are combined with ex situ characterization data.
Lila Randriamananjara, Vincent Rat, Quentin Dubreuil, Patrice Valorge, Simon Goutier, Alain Denoirjean, Olivier Messe, Céline Ruelle, Jean‐Philippe Poli   +8 more
wiley   +1 more source

MODELING OF KOVAZHNY FLOW AND TAYLOR – GREEN VORTEX ON PHYSICS-INFORMED RADIAL BASIS FUNCTION NETWORKS

Модели, системы, сети в экономике, технике, природе и обществе
Background. An analysis of physics-informed neural networks for solving partial differential equations has been conducted, and the advantages of physics-informed radial basis function networks have been demonstrated.
Dmitry A. Stenkin
doaj   +1 more source

Local moving least square-one-dimensional integrated radial basis function networks technique for incompressible viscous flows [PDF]

, 2012
This paper presents a local moving least square-one-dimensional integrated radial basis function networks method for solving incompressible viscous flow problems using stream function-vorticity formulation.
Ngo-Cong, D., Mai-Duy, N., Karunasena, W., Tran-Cong, T.   +3 more
core   +1 more source

Enhanced Strength and Corrosion Resistance of Ti‐13Nb‐12Ta‐10Zr‐4Sn Alloy by Aging Treatment

Advanced Engineering Materials, EarlyView.
This work systematically investigates the effect of aging treatment on mechanical properties and corrosion behavior of vacuum arc‐melted Ti‐13Nb‐12Ta‐10Zr‐4Sn alloy. Owing to the increased α″ martensite, strength and corrosion resistance were significantly enhanced by aging treatment.
Yuhua Li, Rong Zhao, Qian Zhang, Haojie Wang, Yujing Liu, Lai‐Chang Zhang   +5 more
wiley   +1 more source

RbfCon: Construct Radial Basis Function Neural Networks with Grammatical Evolution

Software
Radial basis function networks are considered a machine learning tool that can be applied on a wide series of classification and regression problems proposed in various research topics of the modern world.
Ioannis G. Tsoulos, Ioannis Varvaras, Vasileios Charilogis   +2 more
doaj   +1 more source

Microstructure Reconstruction in Battery Electrodes Using Machine Learning Based on Low‐Voltage Focused Ion Beam–Scanning Electron Microscopy Tomography Images

Advanced Engineering Materials, EarlyView.
Low‐voltage FIB‐SEM tomography combined with a image preprocessing pipeline improves phase contrast and enables reliable machine‐learning segmentation of conductive networks in lithium‐ion battery electrodes. Structural descriptors are extracted from segmented images, done semimanually and automated, and compared.
Lisa Beran, Vincent Nebel, Dominik Perius, Kshitij Kumar, Yannis Heim, Laura Bies, Tobias Kraus   +6 more
wiley   +1 more source

Reconstruction of Daily Sea Surface Temperature Based on Radial Basis Function Networks

Remote Sensing, 2017
A radial basis function network (RBFN) method is proposed to reconstruct daily Sea surface temperatures (SSTs) with limited SST samples. For the purpose of evaluating the SSTs using this method, non-biased SST samples in the Pacific Ocean (10°N–30°N, 115°
Zhihong Liao, Qing Dong, Cunjin Xue, Jingwu Bi, Guangtong Wan   +4 more
doaj   +1 more source