Results 51 to 60 of about 14,713 (239)

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

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

Control of hybrid electromagnetic bearing and elastic foil gas bearing under deep learning.

PLoS ONE, 2020
The hybrid electromagnetic and elastic foil gas bearing is explored based on the radial basis function (RBF) neural network in this study so as to improve its stabilization in work.
Xiangxi Du, Yanhua Sun
doaj   +1 more source

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

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

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

A Comprehensive Comparative Study of Active Learning Schemes for Nanophotonics Design

Advanced Intelligent Discovery, EarlyView.
Active learning (AL) strategies are benchmarked for the binary design of planar multilayer nanophotonic structures. Factorization machines combined with quantum annealing (QA) become effective as dimensionality increases. Hybrid QA provides the strongest results for 100‐layer problems, highlighting the importance of optimization method selection in ...
Serang Jung, Seongmin Kim, Jaehyun Park, Chaeyoung Park, Zhihao Xu, Sanghyo Hwang, Baiqing Ye, Youn sang Kim, Sun‐Kyung Kim, Tengfei Luo, Eungkyu Lee   +10 more
wiley   +1 more source

Research on Soil Erosion Prediction Model Based on RBF Neural Network

Shuitu baochi yanjiu, 2013
The physical mechanism of soil erosion is so complicated that it is difficult to be described by the mathematical mode.According to the characteristic of vagueness,randomness and nonlinear of soil erosion process,the RBF neural network theory and method ...
YI Yan-ping1, LU Wen-xi1, XU Xiao-hong2, HONG De-fa3   +3 more
doaj  

Accelerating Materials Discovery: A Review of Machine Learning in X‐Ray Absorption Spectroscopy

Advanced Intelligent Systems, EarlyView.
This review systematically details how machine learning transforms X‐ray absorption spectroscopy (XAS) analysis. It covers advanced deep learning architectures for structure‐spectra mapping and inverse tasks, while discussing key challenges like the simulation‐to‐reality gap.
Melaku Lake Tegegne, Haodong Yao, Liyuan Wu, Yihe Pang, Fazhi Qi, Lina Zhao   +5 more
wiley   +1 more source

Sports Activity Recognition Using Textile‐Based Sensor Fusion and Complex‐Valued Residual Convolutional Neural Networks

Advanced Intelligent Systems, EarlyView.
Motion artifacts in electrocardiographic signals, conventionally dismissed as noise, are shown to encode discriminative activity information. A smart t‐shirt fusing textile strain sensors with textile ECG electrodes, processed through a complex‐valued residual network, recognizes 12 sport activities.
Nada Al‐azzawi, Munire Sibel Cetin, Asli Tuncay Atalay, Ozgur Atalay, Gökhan Ince   +4 more
wiley   +1 more source