Rapid Focused Spot Scanning Imaging Using Multimode Fiber with a Convolutional Neural Network-Based Phase Modulation by Rongjing Tong, Anni Xu, Hua Shen

“…In this paper, we present a rapid beam-focusing method for multimode fiber (MMF) that integrates a Convolutional Neural Network (CNN) with a Spatial Light Modulator (SLM). …”
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Photovoltaic solar energy prediction using the seasonal-trend decomposition layer and ASOA optimized LSTM neural network model by Venkatachalam Mohanasundaram, Balamurugan Rangaswamy

“…To address these challenges, this research introduces an innovative method that integrates Robust Seasonal-Trend Decomposition (RSTL) with an Adaptive Seagull Optimisation Algorithm (ASOA)-optimized Long Short-Term Memory (LSTM) neural network. Using RSTL to differentiate between time series data into development, seasonal in nature, and residual factors, this methodology addresses SI’s unpredictable nature and intermittent operation and provides the basis for accurate predictions. …”
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Retracted: Characteristics Analysis of Mental Health Data of College Students Based on Convolutional Neural Network and TOPSIS Evaluation Model by Discrete Dynamics in Nature and Society

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A multi-layer neural network-based evaluation of MHD radiative heat transfer in Eyring–Powell fluid model by Muflih Alhazmi, Zahoor Shah, Muhammad Asif Zahoor Raja, Nafisa A. Albasheir, Maryam Jawaid

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Simulating the air quality impact of prescribed fires using graph neural network-based PM2.5 forecasts by Kyleen Liao, Jatan Buch, Kara D. Lamb, Pierre Gentine

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Research on Concrete Beam Damage Detection Using Convolutional Neural Networks and Vibrations from ABAQUS Models and Computer Vision by Xin Bai, Zi Zhang

“…Researchers have already used vibration data and deep learning methods, such as Convolutional Neural Networks (CNNs), to detect structural damage. Moreover, some researchers have employed image-based displacement sensors (such as the template matching and edge detection methods) to obtain structural vibration information. …”
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Adaptive Neural Networks Control Using Barrier Lyapunov Functions for DC Motor System with Time-Varying State Constraints by Lei Ma, Dapeng Li

“…This paper proposes an adaptive neural network (NN) control approach for a direct-current (DC) system with full state constraints. …”
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Developing a Method for Building Business Process Models Based on Graph Neural Networks in the Absence of Task Identifier Data by Oleg Kazakov, Natalya Azarenko, Irina Kozlova

“…The aim of the study is to develop a method of creating business process models through the restoration of links between events recorded in logs in the absence of CaseID data based on graph neural networks. The problem is solved by applying the graph convolutional networks architecture. …”
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Determination of Optimal Drop Height in Free-Fall Shock Test Using Regression Analysis and Back-Propagation Neural Network by Chao-Rong Chen, Chia-Hung Wu, Hsin-Tsrong Lee

“…To improve the conventional approaches, this study proposes the application of regression analysis and back-propagation neural network for determining the most suitable drop height for free-fall shock tests. …”
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Investigating Two-dimensional Horizontal Mesh Grid Effects on the Eulerian Atmospheric Transport Model Using Artificial Neural Network by Amine Ajdour, Brahim Ydir, Houria Bouzghiba, Ishaq Dimeji Sulaymon, Anas Adnane, Dris Ben Hmamou, Kenza Khomsi, Jamal Chaoufi, Gábor Géczi, Radouane Leghrib

“…The second aspect demonstrates: (4) CHIMERE-Artificial Neural Network (CHIMERE-ANN) demonstrates high accuracy in predicting ozone levels for Agadir and Casablanca, achieving improved correlation coefficients of 80% and 94%, respectively, accompanied by a notable decrease in Root Mean Square Error (RMSE) to 7.5 µg m–3 and 7.4 µg m–3. (5) Implementing CHIMERE-ANN with high spatial resolution concentrations (RA3 and RC3) enhances the accuracy of pollutant concentration forecasts. …”
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Finite-Time Cluster Synchronization of Fractional-Order Complex-Valued Neural Networks Based on Memristor with Optimized Control Parameters by Qi Chang, Rui Wang, Yongqing Yang

Subjects: “…coupled memristive neural networks…”
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Flexible multi-fidelity framework for load estimation of wind farms through graph neural networks and transfer learning – ERRATUM by Gregory Duthé, Francisco de N Santos, Imad Abdallah, Wout Weijtjens, Christof Devrient, Eleni Chatzi

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Long Short-Term Memory Recurrent Neural Network for Predicting the Return of Rate Underframe the Fama-French 5 Factor by Bui Thanh Khoa, Tran Trong Huynh

“…Two approaches are employed in the Fama-French model: Long Short Term Memory Recurrent Neural Network (LSTM-RNN) and Maximum Likelihood Estimation (MLE). …”
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Hybrid Technique to Improve the River Water Level Forecasting Using Artificial Neural Network-Based Marine Predators Algorithm by Sarah J. Mohammed, Salah L. Zubaidi, Nadhir Al-Ansari, Hussein Mohammed Ridha, Nabeel Saleem Saad Al-Bdairi

“…This paper proposes a novel hybrid machine learning model based on an artificial neural network (ANN) and the Marine Predators algorithm (MPA) for modeling monthly water levels of the Tigris River in Al-Kut, Iraq. …”
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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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Biosensor response to multi-component mixtures statistical analysis and forecasting by Romas Baronas, Sigitas Būda, Feliksas Ivanauskas, Pranas Vaitkus

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A Tractor Work Position Prediction Method Based on CNN-BiLSTM Under GNSS Signal Denial by Yangming Hu, Liyou Xu, Xianghai Yan, Ningjie Chang, Qigang Wan, Yiwei Wu

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