Results 41 to 50 of about 13,817 (251)
Efficient training of RBF neural networks for pattern recognition [PDF]
IEEE Transactions on Neural Networks, 2001 The problem of training a radial basis function (RBF) neural network for distinguishing two disjoint sets in R(n) is considered. The network parameters can be determined by minimizing an error function that measures the degree of success in the recognition of a given number of training patterns.
F. LAMPARIELLO, SCIANDRONE, MARCO
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Advanced Intelligent Discovery, EarlyView.Exosomes are emerging as powerful biomarkers for disease diagnosis and monitoring. This review highlights the integration of surface‐enhanced Raman spectroscopy with artificial intelligence to enhance molecular fingerprinting of exosomes. Machine learning and deep learning techniques improve spectral interpretation, enabling accurate classification of ...
Munevver Akdeniz +2 more
wiley +1 more source
Actuators, 2023 Modeling errors and external disturbances have significant impacts on the control accuracy of robotic arm trajectory tracking. To address this issue, this paper proposes a novel method, the neural network terminal sliding mode control (ALSSA-RBFTSM ...
Jianguo Duan +3 more
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Topology‐Aware Machine Learning for High‐Throughput Screening of MOFs in C8 Aromatic Separation
Advanced Intelligent Discovery, EarlyView.We screened 15,335 Computation‐Ready, Experimental Metal–Organic Frameworks (CoRE‐MOFs) using a topology‐aware machine learning (ML) model that integrates structural, chemical, pore‐size, and topological descriptors. Top‐performing MOFs exhibit aromatic‐enriched cavities and open metal sites that enable π–π and C–H···π interactions, serving as ...
Yu Li, Honglin Li, Jialu Li, Wan‐Lu Li
wiley +1 more source
Deep Learning‐Assisted Design of Mechanical Metamaterials
Advanced Intelligent Discovery, EarlyView.This review examines the role of data‐driven deep learning methodologies in advancing mechanical metamaterial design, focusing on the specific methodologies, applications, challenges, and outlooks of this field. Mechanical metamaterials (MMs), characterized by their extraordinary mechanical behaviors derived from architected microstructures, have ...
Zisheng Zong +5 more
wiley +1 more source
Research of time-delay control of wireless network based on RBF neural network PID control
Gong-kuang zidonghua, 2013 In view of problems that uncertain time-delay influences on control performance of wireless network control system and normal PID control strategy cannot meet control requirement of network, the paper proposed a time-delay control scheme of wireless ...
SUN Xiao-xi, HUANG You-rui, QU Li-guo
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Advanced Intelligent Discovery, EarlyView.A low‐cost, self‐driving laboratory is developed to democratize autonomous materials discovery. Using this "frugal twin" hardware architecture with Bayesian optimization, the platform rapidly converges to target lower critical solution temperature (LCST) values while self‐correcting from off‐target experiments, demonstrating an accessible route to data‐
Guoyue Xu, Renzheng Zhang, Tengfei Luo
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Journal of Applied Mathematics, 2013 An accurate forecasting method for power generation of the wind energy conversion system (WECS) is urgently needed under the relevant issues associated with the high penetration of wind power in the electricity system. This paper proposes a hybrid method
Wen-Yeau Chang
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Research on location and layout of auto-body sheet metal based on NSGA-Ⅱ and RBF neural network
Journal of Hebei University of Science and Technology, 2019 In order to solve the problem of low efficiency and easy clamping deformation in the location layout design of auto-body sheet metal,alocation layout design method of auto-body sheet metal based on NSGA-Ⅱ and RBF neural network is proposed.With the ...
Peng WANG, Jiachuan XU, Fan CAO, Di LI
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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
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