Optimal adjustment of deep neural network parameters in estimating lost vital sign data in body wireless sensor networks by Aboulfazl Ebrahimi, Mahboubeh Shamsi, Morteza Mohajjel

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How to Identify Patterns of Citywide Dynamic Traffic at a Low Cost? An In-Depth Neural Network Approach with Digital Maps by Li Zhang, Ke Gong, Maozeng Xu, Aixing Li, Yuanxiang Dong, Yong Wang

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M&A Short-Term Performance Based on Elman Neural Network Model: Evidence from 2006 to 2019 in China by Ming Xiao, Xionghui Yang, Ge Li

“…After comparing the five abnormal return (AR) calculation models, it is found that the commonly used market model method and the market adjustment method have statistical defects while the Elman feedback neural network model is capable of good nonlinear prediction ability. …”
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Acute ischemic stroke lesion segmentation in non-contrast CT images using 3D convolutional neural networks by A.V. Dobshik, S.K. Verbitskiy, I.A. Pestunov, K.M. Sherman, Yu.N. Sinyavskiy, A.A. Tulupov, V.B. Berikov

“…Our deep-learning approach is based on the popular 3D U-Net convolutional neural network architecture, which was modified by adding the squeeze-and-excitation blocks and residual connections. …”
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A New Type of Eye Movement Model Based on Recurrent Neural Networks for Simulating the Gaze Behavior of Human Reading by Xiaoming Wang, Xinbo Zhao, Jinchang Ren

“…In contrast to conventional psychology-based eye movement models, ours is based on a recurrent neural network (RNN) to generate a gaze point prediction sequence, by using the combination of convolutional neural networks (CNN), bidirectional long short-term memory networks (LSTM), and conditional random fields (CRF). …”
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Adaptive Output Feedback Control for the Trajectory Tracking of High-Speed Trains with Disturbance Uncertainties on the Basis of Neural Network Observers by Yang Liu, Weidong Li

“…Another neural network model is used to approximate the model uncertainties. …”
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Stabilization to Exponential Input-to-State Stability of a Class of Neural Networks with Delay by Observer-Based Aperiodic Intermittent Control by Mengyue Li, Biwen Li, Yuan Wan

“…Compared with the general neural networks, the state of the neural network investigated is not yet fully available. …”
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Parametric Estimation of Directional Wave Spectra from Moored FPSO Motion Data Using Optimized Artificial Neural Networks by Do-Soo Kwon, Sung-Jae Kim, Chungkuk Jin, MooHyun Kim

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Deep Learning Image Classification Rontgen Dada pada Kasus Covid-19 Menggunakan Algoritma Convolutional Neural Network by Leni Anggraini Susanti, Agus Mohamad Soleh, Bagus Sartono

“… Penelitian ini mengusulkan penggunaan Convolutional Neural Network (CNN) dengan arsitektur VGGNet-19 dan ResNet-50 untuk diagnosis COVID-19 melalui analisis citra rontgen dada. …”
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The Prediction of Metro Shield Construction Cost Based on a Backpropagation Neural Network Improved by Quantum Particle Swarm Optimization by Lanjun Liu, Denghui Liu, Han Wu, Xinyu Wang

“…The rough set theory was used to simplify the system of influencing factors to extract the dominant influencing factors and reduce the number of input variables in the BP neural network. Since the BP neural network easily falls into a local minimum and has a slow convergence speed, QPSO was used to optimize the weights and thresholds of the BP neural network. …”
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Trust as a key element in family mediation during divorce: strategies, practices (supervision experience with the use of neural networks) by V. V. Krivopuskov, I. V. Mkrtumova, O. E. Gracheva

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Design of a flattening filter using Fiber Bragg Gratings for EDFA gain equalization: an artificial neural network application by David Esteban Montoya Alba, Jhonatan Mcniven Cagua Herrera, Gustavo Adolfo Puerto Leguizam´ón

Subjects: “…Artificial neural network…”
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RBF Neural Network Backstepping Sliding Mode Adaptive Control for Dynamic Pressure Cylinder Electrohydraulic Servo Pressure System by Pan Deng, Liangcai Zeng, Yang Liu

“…On this basis, a RBF neural network backstepping sliding mode adaptive control algorithm is designed: using the double sliding mode structure, the two RBF neural networks are used to approximate the uncertainties in the two subsystems, provide design methods of RBF sliding mode adaptive controller of the dynamic pressure cylinder displacement subsystem and RBF backstepping sliding mode adaptive controller of the dynamic pressure cylinder output pressure subsystem, and give the two RBF neural network weight vector adaptive laws, and the stability of the algorithm is proved. …”
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Sistem Kontrol Perangkat Inframerah Menggunakan Speech Recognition dengan Spectrogram dan Convolutional Neural Network Berbasis Mikrokontroler by Irfan Muzakky Nurrizqy, Barlian Henryranu Prasetio, Rekyan Regasari Mardi Putri

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Analisis Efek Augmentasi Dataset dan Fine Tune pada Algoritma Pre-Trained Convolutional Neural Network (CNN) by Theopilus Bayu Sasongko, Haryoko Haryoko, Agit Amrullah

“…Kemajuan teknologi deep learning seringkali berbanding lurus dengan keterkaitan metode yang dapat diandalkan dalam penggunaan jumlah data yang besar. Convolutional Neural Network (CNN) adalah salah satu algoritma deep learning yang paling popular saat ini guna pengolahan citra. …”
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IRSnet: An Implicit Residual Solver and Its Unfolding Neural Network With 0.003M Parameters for Total Variation Models by Yuanhao Gong

Subjects: “…Neural network…”
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NIGWO-iCaps NN: A Method for the Fault Diagnosis of Fiber Optic Gyroscopes Based on Capsule Neural Networks by Nan Lu, Huaqiang Zhang, Chunmei Dong, Hongtao Li, Yu Chen

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Mean-Square Exponential Stability Analysis of Stochastic Neural Networks with Time-Varying Delays via Fixed Point Method by Tianxiang Yao, Xianghong Lai

“…This work addresses the stability study for stochastic cellular neural networks with time-varying delays. By utilizing the new research technique of the fixed point theory, we find some new and concise sufficient conditions ensuring the existence and uniqueness as well as mean-square global exponential stability of the solution. …”
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Simulation and Prediction of Injection Pressure in CO2 Geological Sequestration Based on Improved LSO Algorithm and BP Neural Networks by Miaomiao Liu, Xiaofei Fu, Shanpo Jia, Yongsheng Zhang, Yuying Zhang, Dan Yao

“…In order to avoid the occurrence of caprock integrity damage and gas escape due to injection pressure overrun in CO2 sequestration, an optimized back propagation (BP) neural network model based on Monte Carlo simulation (MCS) and an improved lion swarm optimization (ILSO) algorithm is proposed for the maximum sustainable injection pressure prediction. …”
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DR-Z2AN: dual-recurrent neural network with a tri-channel attention mechanism for financial management prediction by Salem Knifo, Ahmad Alzubi

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