Prediction and Evaluation of Rockburst Based on Depth Neural Network by Jin Zhang, Mengxue Wang, Chuanhao Xi

“…Training through existing data. The neural network model shows that the rockburst risk is closely related to the maximum principal stress. …”
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A Novel Kernel for RBF Based Neural Networks by Wasim Aftab, Muhammad Moinuddin, Muhammad Shafique Shaikh

“…In this work, we introduce a novel RBF artificial neural network (ANN) where the basis function utilizes a linear combination of ED based Gaussian kernel and a cosine kernel where the cosine kernel computes the angle between feature and center vectors. …”
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Flood Forecasting for Small Reservoirs Based on Neural Networks by PENG Wei, XIONG Jiayi, JIANG Xianqun, GAO Yueming

Subjects: “…neural network…”
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Neural Networks in Mechanical System Simulation, Identification, and Assessment by Thomas L. Paez

“…Artificial neural networks (ANNs) have been used in the solution of a variety of mechanical system design, analysis, and control problems. …”
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GuardianMPC: Backdoor-Resilient Neural Network Computation by Mohammad Hashemi, Domenic Forte, Fatemeh Ganji

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Driver Distraction Identification with an Ensemble of Convolutional Neural Networks by Hesham M. Eraqi, Yehya Abouelnaga, Mohamed H. Saad, Mohamed N. Moustafa

“…The system consists of a genetically weighted ensemble of convolutional neural networks; we show that a weighted ensemble of classifiers using a genetic algorithm yields a better classification confidence. …”
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Neural Networks Application for the Data of PID Controller for Acrobot by Nguyen Cong Danh

“…Control an Acrobot system, including Neural Network Application for the data of the PID controller (closed form). …”
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On the Prediction of the Sideslip Angle Using Dynamic Neural Networks by Raffaele Marotta, Salvatore Strano, Mario Terzo, Ciro Tordela

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Methods for Constructing Artificial Neural Networks for Data Classification by L. V. Serebryanaya

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Multilayer magnetic skyrmion devices for spiking neural networks by Aijaz H Lone, Daniel N Rahimi, Hossein Fariborzi, Gianluca Setti

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GTAT: empowering graph neural networks with cross attention by Jiahao Shen, Qura Tul Ain, Yaohua Liu, Banqing Liang, Xiaoli Qiang, Zheng Kou

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Machine learning Hubbard parameters with equivariant neural networks by Martin Uhrin, Austin Zadoks, Luca Binci, Nicola Marzari, Iurii Timrov

“…Here, we present a machine learning model based on equivariant neural networks which uses atomic occupation matrices as descriptors, directly capturing the electronic structure, local chemical environment, and oxidation states of the system at hand. …”
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Closed-form interpretation of neural network classifiers with symbolic gradients by Sebastian J Wetzel

Subjects: “…artificial neural networks…”
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Attention-Based Convolutional Neural Network for Pavement Crack Detection by Haifeng Wan, Lei Gao, Manman Su, Qirun Sun, Lei Huang

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Aircraft Actuator Performance Analysis Based on Dynamic Neural Network by Wathiq Rafa Abed

“…The proposed method starts with the current and vibration signal as failure indicators and a dual-tree complex wavelet transformation (DTCWT) to generate the necessary features. Time-delay neural networks (TDNNs) have been developed for real-time performance monitoring to categorize problems and determine their severity. …”
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Information-Enhanced Graph Neural Network for Transcending Homophily Barriers by Xiao Liu, Lijun Zhang, Hui Guan

Subjects: “…Graph neural networks (GNNs)…”
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Visual Explainable Convolutional Neural Network for Aerodynamic Coefficient Prediction by Yanxuan Zhao, Chengwen Zhong, Fang Wang, Yueqing Wang

“…In this paper, a novel neural network is proposed to predict the aerodynamic forces of airfoils. …”
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Neural network potentials for exploring condensed phase chemical reactivity by Gomez, Axel, de la Puente, Miguel, David, Rolf, Laage, Damien

“…In this tutorial review, we describe the key challenges associated with simulating reactions in condensed phases, we introduce neural network potentials and detail how they can be trained. …”
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Investigation of acquisition of the UWB signals based on BP neural network by YANG Zhi-hua1, ZHANG Qin-yu1, CHEN Ping2, XU Hong-guang1

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Understanding Logical-Shift Error Propagation in Quanvolutional Neural Networks by Marzio Vallero, Emanuele Dri, Edoardo Giusto, Bartolomeo Montrucchio, Paolo Rech

“…Quanvolutional neural networks (QNNs) have been successful in image classification, exploiting inherent quantum capabilities to improve performance of traditional convolution. …”
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