Results 61 to 70 of about 35,631 (308)

Construction of radial basis function networks with diversified topologies

, 2011
In this review we bring together some of our recent work from the angle of the diversified RBF topologies, including three different topologies; (i) the RBF network with tunable nodes; (ii) the Box-Cox output transformation based RBF network (Box-Cox RBF)
Hong, Xia, Harris, C. J., X. Hong, S. Chen, Chen, Sheng, C. J. Harris, Harris, Chris J., Chen, S.   +7 more
core   +1 more source

Triple Junctions as Dislocation‐Like Defects: The Role of Grain Boundary Crystallography Revealed by Experiment and Atomistic Simulation

Advanced Engineering Materials, EarlyView.
Grain boundary triple junctions are an essential ingredient of the microstructure of polycrystalline materials. In this study, a triple junction is observed using atomic‐resolution scanning transmission electron microscopy and characterized. Computer simulations reveal that the junction has a dislocation character that is determined by the joining ...
Tobias Brink, Saba Saood, Peter Schweizer, Jörg Neugebauer, Gerhard Dehm   +4 more
wiley   +1 more source

A Novel Deep Reinforcement Learning Based Extended Fractal Radial Basis Function Network for State‐of‐Charge Estimation

IET Power Electronics
This paper presents a novel deep reinforcement learning based extended fractal radial basis function (DRL‐EFRBF) network for accurate state‐of‐charge (SOC) estimation in lithium iron phosphate (LiFePO4) batteries. Unlike conventional methods such as open
Syed M. Ali, Muhammad Bilal, Ayman Alharbi, Rooh ul Amin   +3 more
doaj   +1 more source

Electroencephalography Artifact Removal using Optimized Radial Basis Function Neural Networks

Majlesi Journal of Electrical Engineering
Electroencephalography (EEG) is a major clinical tool to diagnose, monitor and manage neurological disorders which is mostly affected by artifacts.
Shoorangiz Shams Shamsabad Farahani, Mohammad Mahdi Arefi, Amir Hossein Zaeri   +2 more
doaj   +1 more source

Parameter estimation for stiff equations of biosystems using radial basis function networks

BMC Bioinformatics, 2006
Background The modeling of dynamic systems requires estimating kinetic parameters from experimentally measured time-courses. Conventional global optimization methods used for parameter estimation, e.g.
Sugimoto Masahiro, Kikuchi Shinichi, Matsubara Yoshiya, Tomita Masaru   +3 more
doaj   +1 more source

A tunable radial basis function model for nonlinear system identification using particle swarm optimisation

, 2009
A tunable radial basis function (RBF) network model is proposed for nonlinear system identification using particle swarm optimisation (PSO). At each stage of orthogonal forward regression (OFR) model construction, PSO optimises one RBF unit's centre ...
Harris, C. J., X. Hong, B.L. Luk, Chen, Sheng, C.J. Harris, Harris, Chris J., Harris, C.J., Chen, S., Luk, Bing L., Hong, Xia, S. Chen, Luk, B. L., Hong, X.   +12 more
core   +1 more source

Forecasting foreign exchange rates with adaptive neural networks using radial basis functions and particle swarm optimization [PDF]

, 2013
The motivation for this paper is to introduce a hybrid Neural Network architecture of Particle Swarm Optimization and Adaptive Radial Basis Function (ARBF-PSO), a time varying leverage trading strategy based on Glosten, Jagannathan and Runkle (GJR ...
Sermpinis, G., Karathanasopoulos, A., Dunis, C., Theofilatos, K.   +3 more
core   +1 more source

Swelling‐Programmed Topographical Guidance for Dynamic Spheroid Self‐Assembly via a Mechanochemical Hydrogel Niche

Advanced Functional Materials, EarlyView.
A swelling‐programmed micropatterned hydrogel guides adherent cells through a controlled transition from cell–matrix anchoring to cadherin‐mediated cell–cell compaction, enabling rapid assembly of high‐viability spheroids with defined size and morphology.
Han Gyeol Nam, Seon Yeong Chae, Young Woo Kwon, Hye Jin Heo, Hye Rin Lee, Ji Hyeok Lee, Dong‐Wook Han, Yun Hak Kim, Suck Won Hong   +8 more
wiley   +1 more source

Sparse multioutput radial basis function network construction using combined locally regularised orthogonal least square and D-optimality experimental design

, 2003
A construction algorithm for multioutput radial basis function (RBF) network modelling is introduced by combining a locally regularised orthogonal least squares (LROLS) model selection with a D-optimality experimental design.
Harris, C. J., Hong, X., Harris, C.J., Chen, S.   +3 more
core   +1 more source

On combination of SMOTE and particle swarm optimization based radial basis function classifier for imbalanced problems [PDF]

, 2011
The combination of the synthetic minority oversampling technique (SMOTE) and the radial basis function (RBF) classifier is proposed to deal with classification for imbalanced two-class data.
Xia Hong, Hong, Xia, Harris, C. J., Ming Gao, Sheng Chen, Gao, Ming, Chris J. Harris, Chen, Sheng, Gao, M., Harris, Chris, Chen, S.   +10 more
core   +1 more source