Improved Convolutional Neural Image Recognition Algorithm based on LeNet-5 by Lijie Zhou, Weihai Yu

“…Convolutional neural network (CNN) is a very important method in deep learning, which solves many complex pattern recognition problems. …”
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Accurate Recognition and Simulation of 3D Visual Image of Aerobics Movement by Wenhua Fan, Hyun Joo Min

“…The structure of the deep artificial neural network is similar to the structure of the biological neural network, which can be well applied to the 3D visual image recognition of aerobics movements. …”
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Effect of Bodybuilding and Fitness Exercise on Physical Fitness Based on Deep Learning by Manman Sun, Lijun Wang

“…In this paper, recurrent neural network and gated recurrent neural network are introduced to compare and analyze the data, and the stability of data processing with different activation functions is compared. …”
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Selecting the Best Routing Traffic for Packets in LAN via Machine Learning to Achieve the Best Strategy by Bo Zhang, Rongji Liao

“…Therefore, the use of these elements in building the neural network is worthy, as is the exploitation of the feed forwarding and the backpropagation in the neural network in order to reach the best prediction for the best path. …”
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Intelligent Computer Technology-Driven Mural Pattern Recognition Method by Wenqing Wei, Lei Gao

“…In recent years, as a new image processing technology, deep learning based on a convolutional neural network is widely used in many fields. Using a convolutional neural network to recognize images has become a very active topic. …”
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Design and Application of a Financial Distress Early Warning Model Based on Data Reasoning and Pattern Recognition by Xiaoya Hu

“…The prediction effect of the swarm optimization BP neural network model is better than that of the BP neural network model. …”
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Adaptive Neural Sliding Mode Control of Active Power Filter by Juntao Fei, Zhe Wang

“…A radial basis function (RBF) neural network adaptive sliding mode control system is developed for the current compensation control of three-phase active power filter (APF). …”
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Efficient DoA Tracking of Variable Number of Moving Stochastic EM Sources in Far-Field Using PNN-MLP Model by Zoran Stanković, Nebojša Dončov, Bratislav Milovanović, Ivan Milovanović

“…An efficient neural network-based approach for tracking of variable number of moving electromagnetic (EM) sources in far-field is proposed in the paper. …”
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Spectral Quantitative Analysis Model with Combining Wavelength Selection and Topology Structure Optimization by Qian Wang, Boyan Cai, Yajie Yu, Hui Cao

“…For the proposed method, backpropagation neural network is adopted for building the component prediction model, and the simultaneousness optimization of the wavelength selection and the topology structure of neural network is realized by nonlinear adaptive evolutionary programming (NAEP). …”
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Echoing Mechanism of Juvenile Delinquency Prevention and Occupational Therapy Education Guidance Based on Artificial Intelligence by Fang Hou

“…Two crime type prediction algorithms based on time-crime type count vectorization and dense neural network and crime type prediction based on the fusion of dense neural network and long- and short-term memory neural network are proposed. …”
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Optimization of LMBP high-speed railway wheel size prediction algorithm based on improved adaptive differential evolution algorithm by Yu Zhang, Jiawen Zhang, Lin Luo, Xiaorong Gao

“…Aiming at the shortcomings of back propagation neural network, it is easy to fall into local extreme value. …”
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Frequency Diverse Array Target Localization Based on IPSO-BP by Qinghua Liu, Kai Ding, Bingsen Wu, Quanmin Xie

“…This paper introduces a good learning and predictive method of target localization by using BP neural network on FDA, and FDA-IPSO-BP neural network algorithm is formed. …”
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A Novel Guidance Law for Intercepting a Highly Maneuvering Target by Gang Wu, Ke Zhang

“…The parameters of the RBF neural network are adjusted online in real time, for the purpose of improving the estimation accuracy of the RBF neural network disturbance observer and accelerating its convergence characteristics. …”
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Using machine learning to study the population life quality: methodological aspects by E. V. Shchekotin, В. Л. Гойко, P. A. Basina, B. B. Bakulin

“…The article consistently reviews all stages of the machine learning algorithms application to assess the life quality of the population of the regions of the Russian Federation and the issues of improving neural network accuracy. To train the neural network the authors formed a set of marked-up data extracted from regional communities of the social network “VKontakte”. …”
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Application of differential privacy to sensor data in water quality monitoring task by Audris Arzovs, Sergei Parshutin, Valts Urbanovics, Janis Rubulis, Sandis Dejus

“…This study aims to examine the accuracy of four different neural network model architectures with DP applications. …”
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Design Optimization of Curved Curtain Wall Based on SPEA II-GA-BPNN Algorithm by YiQuan Zou, HaoZhou Huang, XuYong Xia, Xin Wang

“…The trained BP neural network model is used to predict and select the optimal solution in the solution set. …”
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Applications of Deep Learning in the Evaluation and Analysis of College Students’ Mental Health by Lanfeng Zhou

“…Based on this, this paper carries out the research method of convolutional neural network by using the research concept of deep learning. …”
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Deep Learning Image Feature Recognition Algorithm for Judgment on the Rationality of Landscape Planning and Design by Bin Hu

“…Compared with the 65% accuracy rate of the convolutional neural network, the fully convolutional neural network has an accuracy rate of 90.3% for the recognition of landscape elements. …”
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Design and Implementation of a Novel Intelligent Strategy for the Permanent Magnet Synchronous Motor Emulation by Hamed Zeinoddini-Meymand, Salah Kamel, Baseem Khan

“…In this paper, an intelligent neural network-based controller is designed and implemented to control the speed of a permanent magnet synchronous motor (PMSM). …”
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Effect of Learning Rate on the Recognition of Images by M. Hamed, A. El Desouky

“…This paper presents a study for the effect of learning rate on an approach for texture classification and detection based on the neural network principle. This neural network consists of three layers, which are input, output, and hidden layers. …”
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