NEURAL-NETWORK

作品数：41被引量：123H指数：7
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When linear inversion fails:Neural-network optimization for sparse-ray travel-time tomography of a volcanic edifice
《Artificial Intelligence in Geosciences》2024年第1期232-243,共12页Abolfazl Komeazi Georg Rümpker Johannes Faber Fabian Limberger Nishtha Srivastava 
In this study,we present an artificial neural network(ANN)-based approach for travel-time tomography of a volcanic edifice under sparse-ray coverage.We employ ray tracing to simulate the propagation of seismic waves t...
关键词：Volcanic edifice Neural network Deep learning Magma chamber TOMOGRAPHY INVERSION 
Ultra-wide FOV meta-camera with transformerneural-network color imaging methodology
《Advanced Photonics》2024年第5期31-40,共10页Yan Liu Wen-Dong Li Kun-Yuan Xin Ze-Ming Chen Zun-Yi Chen Rui Chen Xiao-Dong Chen Fu-Li Zhao Wei-Shi Zheng Jian-Wen Dong 
supported by the National Key R&D Program of China(Grant No.2023YFB2806800);the National Natural Science Foundation of China(Grant Nos.62035016 and U21A20471);the Guangdong Basic and Applied Basic Research Foundation(Grant No.2023B1515040023);the Guangzhou Science and Technology Program(Grant No.202201011671).
Planar cameras with high performance and wide field of view(FOV)are critical in various fields,requiring highly compact and integrated technology.Existing wide FOV metalenses show great potential for ultrathin optical...
关键词：metalens meta-camera wide field of view neural network color imaging compact imaging device 
Application of neural-network hybrid models in estimating the infection functions of nonlinear epidemic models
《International Journal of Biomathematics》2024年第6期141-159,共19页Chentong Li Changsheng Zhou Junmin Liu Yao Rong 
This work was funded by the GDAS'Project of Science and Technology Development(2021GDASYL-20210103089);Postdoctoral Research Foundation of China(2021M690747);National Natural Science Foundation of China(12001139,61877049 and 11991023);Science and Technology Program of Guangzhou(202007040007);GDAS'Project of Science and Technology Development(2019GDASYL-0502007);Guangdong Provincial Rural Revitalization Strategy Special Fund Project(2019KJ138);Guangdong Basic and Applied Basic Research Foundation(2019A1515110503).
Hybrid neural network models are effective in analyzing time-series data by combining the strengths of neural networks and differential equation models.Although most studies have focused on linear hybrid models,few ha...
关键词：Differential equations epidemic model hybrid model neural network 
A Neural-network-based Alternative Scheme to Include Nonhydrostatic Processes in an Atmospheric Dynamical Core
《Advances in Atmospheric Sciences》2024年第6期1083-1099,I0002,I0003,共19页Yang XIA Bin WANG Lijuan LI Li LIU Jianghao LI Li DONG Shiming XU Yiyuan LI Wenwen XIA Wenyu HUANG Juanjuan LIU Yong WANG Hongbo LIU Ye PU Yujun HE Kun XIA 
supported by the National Science Foundation of China(Grant No.42230606)。
Here,a nonhydrostatic alternative scheme(NAS)is proposed for the grey zone where the nonhydrostatic impact on the atmosphere is evident but not large enough to justify the necessity to include an implicit nonhydrostat...
关键词：neural network nonhydrostatic alternative scheme atmospheric model dynamical core 
A new neural-network-based method for structural damage identification in single-layer reticulated shells
《Frontiers of Structural and Civil Engineering》2024年第1期104-121,共18页Jindong ZHANG Xiaonong GUO Shaohan ZONG Yujian ZHANG 
the financial support provided by the National Natural Science Foundation of China(Grant No.51478335).
Single-layer reticulated shells(SLRSs)find widespread application in the roofs of crucial public structures,such as gymnasiums and exhibition center.In this paper,a new neural-network-based method for structural damag...
关键词：single-layer reticulated shell damage identification neural network convolutional neural network cross-partitioning method 
Neural-network-based fully distributed formation control for nonlinear multi-agent systems with event-triggered communication被引量：2
《Science China(Technological Sciences)》2024年第1期209-220,共12页ZHU GuoLiang LIU KeXin GU HaiBo LÜJinHu 
This work was supported by the National Key R&D Program of China(Grant No.2022YFB3305600);the National Natural Science Foundation of China(Grant Nos.62103015,62141604 and 92067204);the Fundamental Research Funds for Central Universities of China(Grant No.YWF-23-03-QB-019).
This paper investigates the consensus-based formation control problem for multi-agent systems with unknown nonlinear dynamics.To achieve the desired formation,we propose two formation controllers to achieve the desire...
关键词：formation control neural network adaptive control event-triggered communication multi-agent systems 
Neural-Network-Based Adaptive Finite-Time Control for a Two-Degree-of-Freedom Helicopter System With an Event-Triggering Mechanism被引量：1
《IEEE/CAA Journal of Automatica Sinica》2023年第8期1754-1765,共12页Zhijia Zhao Jian Zhang Shouyan Chen Wei He Keum-Shik Hong 
supported in part by the National Natural Science Foundation of China(62273112,62061160371,61933001,51905115);the Science and Technology Planning Project of Guangzhou City(202201010758);the Guangzhou University-Hong Kong University of Science and Technology Joint Research Collaboration Fund(YH202205);the Open Research Fund from the Guangdong Laboratory of Artificial Intelligence and Digital Economy(Shenzhen(SZ))(GML-KF-22-27);the Korea Institute of Energy Technology Evaluation and Planning Through the Auspices of the Ministry of Trade,Industry and Energy,Republic of Korea(20213030020160)。
Helicopter systems present numerous benefits over fixed-wing aircraft in several fields of application.Developing control schemes for improving the tracking accuracy of such systems is crucial.This paper proposes a ne...
关键词：Adaptive neural-network control event-triggering mechanism(ETM) finite time two-degree-of-freedom helicopter 
An Efficient Neural-Network and Finite-Difference Hybrid Method for Elliptic Interface Problems with Applications被引量：1
《Communications in Computational Physics》2023年第4期1090-1105,共16页Wei-Fan Hu Te-Sheng Lin Yu-Hau Tseng Ming-Chih Lai 
the supports by National Science and Technology Council,Taiwan,under the research grants 111-2115-M-008-009-MY3,111-2628-M-A49-008-MY4,111-2115-M-390-002,and 110-2115-M-A49-011-MY3,respectively;the supports by National Center for Theoretical Sciences,Taiwan.
A new and efficient neural-network and finite-difference hybrid method is developed for solving Poisson equation in a regular domain with jump discontinuities on embedded irregular interfaces.Since the solution has lo...
关键词：Neural networks sharp interface method fast direct solver elliptic interface problem Stokes equations 
Artificial-neural-network-based storage method for three-dimensional temperature field data during friction stir welding被引量：1
《China Welding》2022年第3期1-7,共7页Han Ce Zhang Qian Shi Qingyu Tang Tianxiang Liu Xin Zhang Gong Chen Gaoqiang 
supported by the National Natural Science Foundation of China(Grant No.52175334);the Award Cultivation Foundation from Beijing Institute of Petrochemical Technology(Project No.BIPTACF-009).
In this paper,a new storage method for the three-dimensional temperature field data based on artificial neural network(ANN)was proposed.A multilayer perceptron that takes the coordinate(x,y,z)as inputs and temperature...
关键词：friction stir welding temperature field artificial neural network numerical simulation 
Experimental Performance Evaluation and Artificial-Neural-Network Modeling of ZnO-CuO/EG-W Hybrid Nanofluids被引量：1
《Fluid Dynamics & Materials Processing》2022年第3期629-646,共18页Yuling Zhai Long Li Zihao Xuan Mingyan Ma Hua Wang 
This project is supported by Yulingn Zhai and the National Natural Science Foundation of China(No.51806090);the Basic Research Project of Yunnan Province(No.202001AT070081).
The thermo-physical properties of nanofluids are highly dependent on the used base fluid.This study explores the influence of the mixing ratio on the thermal conductivity and viscosity of ZnO-CuO/EG(ethylene glycol)-W...
关键词：Hybrid nanofluids base fluid ratio VISCOSITY thermal conductivity ANN model 
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