Convolutional Recurrent Neural Network for Fault Diagnosis of High-Speed Train Bogie by Kaiwei Liang, Na Qin, Deqing Huang, Yuanzhe Fu

“…Notice that convolutional neural networks (CNNs) are powerful in extracting high-level local features and that recurrent neural networks (RNNs) are capable of learning long-term context dependencies in vibration signals. …”
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New Results on Passivity Analysis for Uncertain Neural Networks with Time-Varying Delay by Xueying Shao, Qing Lu, Hamid Reza Karimi, Jin Zhu

“…The paper investigates the stability and passivity analysis problems for a class of uncertain neural networks with time-delay via delta operator approach. …”
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Deep learning in microbiome analysis: a comprehensive review of neural network models by Piotr Przymus, Krzysztof Rykaczewski, Adrián Martín-Segura, Jaak Truu, Enrique Carrillo De Santa Pau, Mikhail Kolev, Mikhail Kolev, Irina Naskinova, Aleksandra Gruca, Alexia Sampri, Alexia Sampri, Marcus Frohme, Alina Nechyporenko, Alina Nechyporenko

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Air Pollution Forecasting Using Artificial and Wavelet Neural Networks with Meteorological Conditions by Qingchun Guo, Zhenfang He, Shanshan Li, Xinzhou Li, Jingjing Meng, Zhanfang Hou, Jiazhen Liu, Yongjin Chen

Subjects: “…Wavelet artificial neural network…”
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Innovation of Teaching Method of Digital Media Art Based on Convolutional Neural Network by Yumei Liu

“…In order to improve the effect of digital media art teaching, this study combines the neural network algorithm to carry out the innovation of digital media art teaching resource management and teaching method innovation. …”
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Children Tracking System Based on ZigBee Wireless Network and Neural Network by Nadia Ahmed, Sadik Kamel Gharghan, Ammar Hussein Mutlag, M. G. M. Abdolrasol

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Application of Quantum Recurrent Neural Network in Low-Resource Language Text Classification by Wenbin Yu, Lei Yin, Chengjun Zhang, Yadang Chen, Alex X. Liu

Subjects: “…quantum recurrent neural network…”
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Application of Artificial Neural Network for Damage Detection in Planetary Gearbox of Wind Turbine by Marcin Strączkiewicz, Tomasz Barszcz

“…To overcome this obstacle, it is proposed to detect a fault development with Artificial Neural Network (ANN) and further observation of linear regression parameters calculated on the estimation error between healthy and unknown condition. …”
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Determining the Thermal Conductivity of Clay during the Freezing Process by Artificial Neural Network by Xiuling Ren, Yanhui You, Qihao Yu, Guike Zhang, Pan Yue, Mingyang Jin

“…By measuring the thermal conductivity of clay using a transient hot-wire method in the laboratory, the influential factors of the thermal conductivity of soils during the freezing process were analyzed, and a predictive model of thermal conductivity was developed with an artificial neural network (ANN) technology. The results show that the variation of thermal conductivity can be divided into three stages with decreasing temperature, positive temperature stage, transition stage, and negative temperature stage. …”
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Utilizing Artificial Neural Network for Load Prediction Caused by Fluid Sloshing in Tanks by Hossein Goudarzvand Chegini, Gholamreza Zarepour

“…The backpropagation of the error algorithm was then used to apply the two multilayer feed-forward neural networks and the recurrent neural network. The findings of the SPH process are employed in the training and testing of neural networks. …”
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Wavelet Denoising of Vehicle Platform Vibration Signal Based on Threshold Neural Network by Mingzhu Li, Zhiqian Wang, Jun Luo, Yusheng Liu, Sheng Cai

“…A method to denoise the VPVS is proposed based on the wavelet coefficients thresholding and threshold neural network (TNN). According to the characteristics of VPVS, a novel thresholding function is constructed, and then its optimized threshold is selected through unsupervised learning of TNN. …”
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Graph Neural Networks in Brain Connectivity Studies: Methods, Challenges, and Future Directions by Hamed Mohammadi, Waldemar Karwowski

Subjects: “…graph neural networks (GNNs)…”
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A multiobjective continuation method to compute the regularization path of deep neural networks by Augustina Chidinma Amakor, Konstantin Sonntag, Sebastian Peitz

“…Sparsity is a highly desired feature in deep neural networks (DNNs) since it ensures numerical efficiency, improves the interpretability (due to the smaller number of relevant features), and robustness. …”
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Relationship between Cognitive Learning Psychological Classification and Neural Network Design Elements by Xing Yang, Tingjun Yong, Meihua Li, Wenying Wang, Huichun Xie, Jinping Du

“…This article first analyzes the research background of the design elements of cognitive psychology and neural networks at home and abroad, roughly understands the research status and research background of these two courses at home and abroad, and discusses the application of cognitive psychology to neural networks. …”
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Optimalisasi Hyper Parameter Convolutional Neural Networks Menggunakan Ant Colony Optimization by Fian Yulio Santoso, Eko Sediyono, Hindriyanto Dwi Purnomo

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Neural Network L1 Adaptive Control of MIMO Systems with Nonlinear Uncertainty by Hong-tao Zhen, Xiao-hui Qi, Jie Li, Qing-min Tian

“…The auxiliary compensation controller is designed to approximate the unknown nonlinear functions by MIMO RBF neural networks to suppress the influence of uncertainties. …”
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High-Performance Inverse Artificial Neural Network Controller for Asynchronous Motor Control by Benyekhlef Kada, Mourad Hebali, Ibrahim Farouk Bouguenna, Benaoumeur Ibari, Menouer Bennaoum

“…These inverse artificial neural networks have been learned from conventional control system (PI controller and vector control) data using MATLAB software. …”
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Neural network as a mirror of social attitudes: analysis of distortions in generative images by A. G. Tertyshnikova, U. O. Pavlova, M. D. Starovoytova

“…The article is devoted to the consideration of neural network generative technologies as a marker of social stereotypes and attitudes. …”
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Image Edge Detection Algorithm Based on Fuzzy Radial Basis Neural Network by Lin Feng, Jian Wang, Chao Ding

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Loss shaping enhances exact gradient learning with Eventprop in spiking neural networks by Thomas Nowotny, James P Turner, James C Knight

Subjects: “…spiking neural network…”
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