Results 51 to 60 of about 13,817 (251)

Parameter-Tunable RBF Neural Network Control Facing Dual-Joint Manipulators

Journal of Robotics, 2022
In order to improve the parameter control effect of the double-joint manipulator, this paper combines the RBF neural network to control the parameters of the double-joint manipulator and the command filtering backstep impedance control method based on ...
Weiying Xu
doaj   +1 more source

Gaussian Process Regression–Neural Network Hybrid with Optimized Redundant Coordinates: A New Simple Yet Potent Tool for Scientist's Machine Learning Toolbox

Advanced Intelligent Discovery, EarlyView.
A machine learning method, opt‐GPRNN, is presented that combines the advantages of neural networks and kernel regressions. It is based on additive GPR in optimized redundant coordinates and allows building a representation of the target with a small number of terms while avoiding overfitting when the number of terms is larger than optimal.
Sergei Manzhos, Manabu Ihara
wiley   +1 more source

Data Glove Gesture Ｒecognition Algorithm Based on GL-ＲBF Neural Network Optimization

Journal of Harbin University of Science and Technology, 2017
In order to solve the problem of accuracy and real-time in the process of gesture recognition of 5DT data glove，a hybrid optimization method of ＲBF(Ｒadial Basis Function) neural network gesture recognition is proposed based on LM(Levenberg Marquardt ...
LI Dong-jie, LI Yang-yang, YANG Liu
doaj   +1 more source

Evaluating Three Foundation Potentials for Predicting Selected Properties of the Co–Ni–Ru Alloy System

Advanced Intelligent Discovery, EarlyView.
Distributions of intrinsic stacking fault energies (ISFE) among different slip planes in the face‐centered cubic Co2Ni2Ru alloy, predicted by three foundation potentials (DPA, Orb, and SevenNet) and density functional theory (DFT) calculations. This study evaluates the efficacy of three foundation potentials (FPs)—SevenNet, DPA, and Orb—in predicting ...
Subah Mubassira, Thu Nguyen, Anvesh Nathani, Shoutian Sun, Ming Hu, Yanqing Su, Bin Wang, Iman Ghamarian, Shuozhi Xu   +8 more
wiley   +1 more source

A fault line selection method for small current grounding system

Gong-kuang zidonghua, 2013
In view of problem that fault line selection method for small current grounding system is difficult to be suitable for different grounding modes, the paper proposed a fault line selection method for small current grounding system based on RBF neural ...
SHI Dan, SHAO Ru-ping, XU Ju
doaj   +1 more source

Deep Learning–Based Extraction of Promising Material Groups and Common Features from High‐Dimensional Data: A Case of Optical Spectra of Inorganic Crystals

Advanced Intelligent Discovery, EarlyView.
We report a novel interpretation method for deep learning models based on feature extraction and clustering. Applying this method to an atomistic line graph neural network (ALIGNN) model trained on optical absorption spectra of 2,681 inorganic compounds obtained from first‐principles calculations, we successfully identify key factors underlying ...
Akira Takahashi, Yu Kumagai, Arata Takamatsu, Fumiyasu Oba   +3 more
wiley   +1 more source

Large‐Scale Machine Learning to Screen for Small‐Molecule Senolytics

Advanced Intelligent Discovery, EarlyView.
A consistent workflow underpins all experiments in this study. A dedicated model‐selection dataset first identifies optimal hyperparameters for each algorithm. Models are then trained and rigorously evaluated on independent sets of molecules using the senolytic ratio SR. Comprehensive hyperparameter exploration across SMILES representations, task types,
Alexis Dougha, Jesus Gil, Pedro J. Ballester   +2 more
wiley   +1 more source

Accelerating Discovery of Organic Molecular Crystals via Materials Informatics and Autonomous Experiments

Advanced Intelligent Discovery, EarlyView.
Materials informatics and autonomous experimentation are transforming the discovery of organic molecular crystals. This review presents an integrated molecule–crystal–function–optimization workflow combining machine learning, crystal structure prediction, and Bayesian optimization with robotic platforms.
Takuya Taniguchi, Kazuki Ishizaki, Ryo Fukasawa   +2 more
wiley   +1 more source

Optimization of modeling and temperature control of air-cooled PEMFC based on TLBO-DE

Energy and AI
The temperature control of the air-cooled proton exchange membrane fuel cell (PEMFC) is important for effective and safe operation. To develop a practical and precise controller, this study combines the Radial Basis Function (RBF) neural network with ...
Pu He, Jun-Hong Chen, Chen-Zi Zhang, Zi-Yan Yu, Ming-Yang Wang, Jun-Yu Chen, Jia-Le Song, Yu-Tong Mu, Kun-Ying Gong, Wen-Quan Tao   +9 more
doaj   +1 more source

Retinal Vessel Segmentation: A Comprehensive Review From Classical Methods to Deep Learning Advances (1982–2025)

Advanced Intelligent Systems, EarlyView.
Four decades of retinal vessel segmentation research (1982–2025) are synthesized, spanning classical image processing, machine learning, and deep learning paradigms. A meta‐analysis of 428 studies establishes a unified taxonomy and highlights performance trends, generalization capabilities, and clinical relevance.
Avinash Bansal, Jan Kubíček, Jana Bahrová, Alice Varyšová, Martin Augustýnek, Marek Penhaker, Juraj Timkovič   +6 more
wiley   +1 more source