NEURAL_NETWORK_MODEL

作品数：126被引量：238H指数：7
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A Basis Function Generation Based Digital Predistortion Concurrent Neural Network Model for RF Power Amplifiers
《ZTE Communications》2025年第1期71-77,共7页SHAO Jianfeng HONG Xi WANG Wenjie LIN Zeyu LI Yunhua 
supported by ZTE Industry-University-Institute Cooperation Funds under Grant No.HC-CN-20220722010。
This paper proposes a concurrent neural network model to mitigate non-linear distortion in power amplifiers using a basis function generation approach.The model is designed using polynomial expansion and comprises a f...
关键词：basis function generation digital predistortion generalized memory polynomial dynamic deviation reduction neural network 
An Arrhythmia Intelligent Recognition Method Based on a Multimodal Information and Spatio-Temporal Hybrid Neural Network Model
《Computers, Materials & Continua》2025年第2期3443-3465,共23页Xinchao Han Aojun Zhang Runchuan Li Shengya Shen Di Zhang Bo Jin Longfei Mao Linqi Yang Shuqin Zhang 
supported by The Henan Province Science and Technology Research Project(242102211046);the Key Scientific Research Project of Higher Education Institutions in Henan Province(25A520039);theNatural Science Foundation project of Zhongyuan Institute of Technology(K2025YB011);the Zhongyuan University of Technology Graduate Education and Teaching Reform Research Project(JG202424).
Electrocardiogram (ECG) analysis is critical for detecting arrhythmias, but traditional methods struggle with large-scale Electrocardiogram data and rare arrhythmia events in imbalanced datasets. These methods fail to...
关键词：Multimodal learning spatio-temporal hybrid graph convolutional network data imbalance ECG classification 
Physics informed neural network model for multi-particle interaction forces
《Particuology》2025年第1期126-138,共13页Yuanye Zhou Hongqiang Wang Borun Wu LiGe Wang Xizhong Chen 
support from National Natural Science Foundation of China(grant No.22308212);Science and Technology Innovation Committee of Shenzhen Municipality(grant Nos.RCBS 20200714114910354,JCYJ 20220530141016036);the fruitful discussion with Dr.Jerol Soibam from Malardalen University.
The discrete element method(DEM)model calculates interaction forces between each pair of particles.However,it becomes computational expensive especially when the number of particles is large.In this study,a novel arti...
关键词：Artificial neural network ResNet PINN MULTIPHASE DEM Particle interaction force 
A 3D convolutional neural network model with multiple outputs for simultaneously estimating the reactive transport parameters of sandstone from its CT images
《Artificial Intelligence in Geosciences》2024年第1期310-319,共10页Haiying Fu Shuai Wang Guicheng He Zhonghua Zhu Qing Yu Dexin Ding 
supported by the National Natural Science Foundation of China (12105139 and 42277264);National Key Research and Development Program of China (2021YFC2902104);Education Department of Hunan Province (21B0446).
Porosity,tortuosity,specific surface area(SSA),and permeability are four key parameters of reactive transport modeling in sandstone,which are important for understanding solute transport and geochemical reaction pro-c...
关键词：Reactive transport CNN model with multiple outputs SANDSTONE TORTUOSITY PERMEABILITY 
Stock return prediction with multiple measures using neural network models被引量：1
《Financial Innovation》2024年第1期1073-1106,共34页Cong Wang 
In the field of empirical asset pricing,the challenges of high dimensionality,non-linear relationships,and interaction effects have led to the increasing popularity of machine learning(ML)methods.This study investigat...
关键词：Neural network model Stock return Macroeconomic conditions Factor model 
A Framework of LSTM Neural Network Model in Multi-Time Scale Real-Time Prediction of Ship Motions in Head Waves
《船舶力学》2024年第12期1803-1819,共17页CHEN Zhan-yang ZHAN Zheng-yong CHANG Shao-ping XU Shao-feng LIU Xing-yun 
山东省自然科学基金面上项目(ZR2024ME139);航空科学基金(2024M074189001);工业装备结构分析国家重点实验室开放基金资助项目(GZ23112)。
Ship motions induced by waves have a significant impact on the efficiency and safety of offshore operations.Real-time prediction of ship motions in the next few seconds plays a crucial role in performing sensitive act...
关键词：deep learning LSTM ship motion real-time prediction irregular waves 
Investigation Study of Structure Real Load Spectra Acquisition and Fatigue Life Prediction Based on the Optimized E cient Hinging Hyperplane Neural Network Model
《Chinese Journal of Mechanical Engineering》2024年第6期628-648,共21页Lin Zhu Benao Xing Xingbao Li Min Chen Minping Jia 
Supported by National Natural Science Foundation of China(Grant No.51805447);Natural Science Foundation of Jiangsu Higher Education of China(Grant No.22KJB460010);Jiangsu Provincial Innovation and Promotion Project of Forestry Science and Technology of China(Grant No.LYKJ[2023]06);Yangzhou Science and Technology Plan(City School Cooperation Project)of China(Grant No.YZ2022193);Cyan Blue Project of Yangzhou University of China。
In the realm of engineering practice,various factors such as limited availability of measurement data and complex working conditions pose significant challenges to obtaining accurate load spectra.Thus,accurately predi...
关键词：Efficient hinging hyperplane neural network model ANOVA decomposition Load spectra optimization Optimal parameter Fatigue life prediction 
Radial basis function neural network and overlay sampling uniform design toward polylactic acid molecular weight prediction
《Chinese Journal of Chemical Engineering》2024年第11期214-221,共8页Jiawei Wu Zhihong Chen Zhongwen Si Xiaoling Lou Junxian Yun 
funded by the Zhejiang Provincial Natural Science Foundation of China(LD21B060001);the National Natural Science Foundation of China(22078296,21576240).
Polylactic acid(PLA)is a potential polymer material used as a substitute for traditional plastics,and the accurate molecular weight distribution range of PLA is strictly required in practical applications.Therefore,ex...
关键词：Polylactic acid Molecular weight prediction Overlay sampling uniform design Neural network model 
Seasonal Short-Term Load Forecasting for Power Systems Based on Modal Decomposition and Feature-Fusion Multi-Algorithm Hybrid Neural Network Model
《Energy Engineering》2024年第11期3461-3486,共26页Jiachang Liu Zhengwei Huang Junfeng Xiang Lu Liu Manlin Hu 
To enhance the refinement of load decomposition in power systems and fully leverage seasonal change information to further improve prediction performance,this paper proposes a seasonal short-termload combination predi...
关键词：Short-term load forecasting seasonal characteristics refined composite multiscale fuzzy entropy(RCMFE) max-relevance and min-redundancy(mRMR) bidirectional long short-term memory(BiLSTM) hyperparameter search 
Application of a neural network model with multimodal fusion for fluorescence spectroscopy
《Nuclear Science and Techniques》2024年第10期135-148,共14页Lin Tang Shuang Zhou Kai-Bo Shi Hong-Tao Shen Lei You 
supported by the Open Project of Guangxi Key Laboratory of Nuclear Physics and Nuclear Technology(No.NLK2022-05);the Central Government Guidance Funds for Local Scientific and Technological Development,China(No.Guike ZY22096024);the Sichuan Natural Science Youth Fund Project(No.2023NSFSC1366);Key R&D Projects of Sichuan Provincial Department of Science and Technology(No.2023YFG0287);the Open Research Fund of National Engineering Research Center for Agro-Ecological Big Data Analysis&Application,Anhui University(No.AE202209);the National Natural Science Youth Foundation of China(No.12305214);the Vanadium and Titanium Resource Comprehensive Utilization Key Laboratory of Sichuan Province(No.2023FTSZ03);the Key Laboratory of Interior Layout optimization and Security,Institutions of Higher Education of Sichuan Province(No.2023SNKJ-01)。
In energy-dispersive X-ray fluorescence spectroscopy,the estimation of the pulse amplitude determines the accuracy of the spectrum measurement.The error generated by the amplitude estimation of the pulse output distor...
关键词：UNet Long-and short-term memory Pulse distortion Pulse height estimation Fluorescent spectroscopy 
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