Ultra-Low Static Power Circuits Addressing the Fan-Out Problem of Analog Neuron Circuits in Spiking Neural Networks by Jonghyuk Park, Woo Young Choi

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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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Adaptive Hierarchical Multi-Headed Convolutional Neural Network With Modified Convolutional Block Attention for Aerial Forest Fire Detection by Md. Najmul Mowla, Davood Asadi, Shamsul Masum, Khaled Rabie

“…Effective detection and classification of forest fire imagery are critical for timely and efficient wildfire management. Convolutional Neural Networks (CNNs) have demonstrated potential in this domain but encounter limitations when addressing varying scales, resolutions, and complex spatial dependencies inherent in wildfire datasets. …”
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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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Epilepsy Diagnosis from EEG Signals Using Continuous Wavelet Transform-Based Depthwise Convolutional Neural Network Model by Fırat Dişli, Mehmet Gedikpınar, Hüseyin Fırat, Abdulkadir Şengür, Hanifi Güldemir, Deepika Koundal

“…<b>Methods:</b> This study proposes a continuous wavelet transform-based depthwise convolutional neural network (DCNN) for epilepsy diagnosis. The 35-channel EEG signals were transformed into 35-channel images using continuous wavelet transform. …”
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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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Glacial lakes outburst susceptibility and risk in the Eastern Himalayas using analytical hierarchy process and backpropagation neural network models by Sandeep Kumar Mondal, Jyotindra Narayan, Chitesh Sharma, Rishikesh Bharti, Santosha Kumar Dwivedy, Pinaki Roy Chowdhury, Ramesh P. Singh

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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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A Classifier Model Using Fine-Tuned Convolutional Neural Network and Transfer Learning Approaches for Prostate Cancer Detection by Murat Sarıateş, Erdal Özbay

“…Methods: In this study, a basic convolutional neural network (CNN) model was developed and subsequently optimized using techniques such as L2 regularization, Tanh activation, dropout, and early stopping to enhance its performance. …”
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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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Alzheimer’s disease recognition using graph neural network by leveraging image-text similarity from vision language model by Byounghwa Lee, Jeong-Uk Bang, Hwa Jeon Song, Byung Ok Kang

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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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Study on the Multi-parameter Inversion of Reservoir Water Quality Based on GF-1 WFV Image and Neural Network Model by ZHENG Yanhui, ZHANG Yuanbo, HE Yanhu

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Defect detection of wire rope for oil well based on adaptive angle by Zhang Jijun, Meng Xiangqing

Subjects: “…BP neural network…”
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