Applying Big Data Based Deep Learning System to Intrusion Detection by Wei Zhong, Ning Yu, Chunyu Ai

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Link Scheduling in Satellite Networks via Machine Learning Over Riemannian Manifolds by Joarder Jafor Sadique, Imtiaz Nasim, Ahmed S. Ibrahim

Subjects: “…Convolutional neural network…”
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Secure Image Reconstruction using Deep Learning-based Autoencoder with Integrated Encryption Layers by Wurood Abd Ali

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NeuroSight: A Deep‐Learning Integrated Efficient Approach to Brain Tumor Detection by Shafayat Bin Shabbir Mugdha, Mahtab Uddin

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Harnessing the Influence of Pressure and Nutrients on Biological CO₂ Methanation Using Response Surface Methodology and Artificial Neural Network—Genetic Algorithm Approaches by Alexandros Chatzis, Konstantinos N. Kontogiannopoulos, Nikolaos Dimitrakakis, Anastasios Zouboulis, Panagiotis G. Kougias

“…Response Surface Methodology (RSM) and Artificial Neural Network (ANN)—Genetic Algorithm (GA) approaches were employed to model and optimize the process. …”
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Methylene Blue Adsorption BY UV-Treated Graphene Oxide Nanoparticles (UV/n-GO): Modeling and Optimization Using Response Surface Methodology and Artificial Neural Networks by M. Venkata Ratnam, Manikkampatti Palanisamy Murugesan, Srikanth Komarabathina, S. Samraj, Mohammedsani Abdulkadir, Muktar Abdu Kalifa

“…Furthermore, the batch adsorption studies were modelled using response surface modelling (RSM) and artificial neural networks (ANNs). Investigations employing FTIR, XRD, and SEM were carried out to characterize the adsorbent. …”
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Modeling and Analysis of Mechanical Properties of Aluminium Alloy (A413) Processed through Squeeze Casting Route Using Artificial Neural Network Model and Statistical Technique by R. Soundararajan, A. Ramesh, S. Sivasankaran, A. Sathishkumar

“…Artificial Neural Network (ANN) approach was used for predicting and analyzing the mechanical properties of A413 aluminum alloy produced by squeeze casting route. …”
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Strategi Penanganan Imbalance Class Pada Model Klasifikasi Penerima Kartu Indonesia Pintar Kuliah Berbasis Neural Network Menggunakan Kombinasi SMOTE dan ENN by Zaqiatud Darojah, Ronny Susetyoko, Nana Ramadijanti

“…This study aims to build the classification model for KIP Kuliah recipients using Neural Network (NN) which can be utilized by universities in selecting prospective KIP Kuliah recipients students. …”
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Enhanced Hyperspectral Forest Soil Organic Matter Prediction Using a Black-Winged Kite Algorithm-Optimized Convolutional Neural Network and Support Vector Machine by Yun Deng, Lifan Xiao, Yuanyuan Shi

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Forecasting Daily Precipitation Using Hybrid Model of Wavelet-Artificial Neural Network and Comparison with Adaptive Neurofuzzy Inference System (Case Study: Verayneh Station, Nahavand) by Abazar Solgi, Vahid Nourani, Amir Pourhaghi

“…Recently artificial neural network (ANN) as a nonlinear interextrapolator is extensively used by hydrologists for precipitation modeling as well as other fields of hydrology. …”
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Wear Behavior Analysis and Gated Recurrent Unit Neural Network Prediction of Coefficient of Friction in Al10Cu-B₄C Composites by Mihail Kolev, Ludmil Drenchev, Veselin Petkov, Rositza Dimitrova, Krasimir Kolev, Boris Yanachkov

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An Artificial Intelligence Method for Asphalt Pavement Pothole Detection Using Least Squares Support Vector Machine and Neural Network with Steerable Filter-Based Feature Extraction by Nhat-Duc Hoang

“…A data set consisting of 200 image samples has been collected to train and validate the predictive performance of two machine learning algorithms including the least squares support vector machine (LS-SVM) and the artificial neural network (ANN). Experimental results obtained from a repeated subsampling process with 20 runs show that both LS-SVM and ANN are capable methods for pothole detection with classification accuracy rate larger than 85%. …”
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Dynamic Neural Network States During Social and Non-Social Cueing in Virtual Reality Working Memory Tasks: A Leading Eigenvector Dynamics Analysis Approach by Pinar Ozel

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Modeling of CO2 solubility and partial pressure in blended diisopropanolamine and 2-amino-2-methylpropanol solutions via response surface methodology and artificial neural network by Zohreh Khoshraftar

“…Abstract In this study, Response Surface Methodology (RSM) and Artificial Neural Networks (ANN) were developed to estimate the equilibrium solubility and partial pressure of CO2 in blended aqueous solutions of diisopropanolamine (DIPA) and 2-amino-2-methylpropanol (AMP). …”
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Convolutional neural networks for accurate real-time diagnosis of oral epithelial dysplasia and oral squamous cell carcinoma using high-resolution in vivo confocal microscopy by Rishi S. Ramani, Ivy Tan, Lindsay Bussau, Lorraine A. O’Reilly, John Silke, Christopher Angel, Antonio Celentano, Lachlan Whitehead, Michael McCullough, Tami Yap

“…To analyse the 9168 images frames obtained, three tandem applied pre-trained Inception-V3 convolutional neural network (CNN) models were developed using transfer learning in the PyTorch framework. …”
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Anomaly Detection and Root Cause Analysis for Energy Consumption of Medium and Heavy Plate: A Novel Method Based on Bayesian Neural Network with Adam Variational Inference by Qiang Guo, Fenghe Li, Hengwen Liu, Jin Guo

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A predefined-time radial basis function (RBF) neural network tracking control method considering actuator faults for a new type of spraying robot by J. Zhao, J. Zhao, Y. Li, Y. Li, Y. Li, B. Pei, Z. Yu, Z. Dong

“…Focusing on the problem of tracking control of a multi-joint robot with uncertain information, such as modeling uncertainty and random interference, a predefined-time radial basis function (RBF) neural network tracking control (PRC) method considering actuator fault is proposed for a new spraying robot. …”
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Reactive Power Control of Single-Stage Three-Phase Photovoltaic System during Grid Faults Using Recurrent Fuzzy Cerebellar Model Articulation Neural Network by Faa-Jeng Lin, Kuang-Chin Lu, Hsuan-Yu Lee

“…Furthermore, the control of active and reactive power is designed using a two-dimensional recurrent fuzzy cerebellar model articulation neural network (2D-RFCMANN). In addition, the online learning laws of 2D-RFCMANN are derived according to gradient descent method with varied learning-rate coefficients for network parameters to assure the convergence of the tracking error. …”
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State of charge estimation of lithium-ion battery based on state of temperature estimation using weight clustered-convolutional neural network-long short-term memory by Chaoran Li, Sichen Zhu, Liuli Zhang, Xinjian Liu, Menghan Li, Haiqin Zhou, Qiang Zhang, Zhonghao Rao

“…And weight clustered-convolutional neural network-long short-term memory (WC-CNN-LSTM) is proposed to achieve high accuracy SOT and SOC estimation with small model sizes. …”
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Investigating Feed-Forward Back-Propagation Neural Network with Different Hyperparameters for Inverse Kinematics of a 2-DoF Robotic Manipulator: A Comparative Study by Rania Bouzid, Jyotindra Narayan, Hassène Gritli

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