Optimal Learning Behavior Prediction System Based on Cognitive Style Using Adaptive Optimization-Based Neural Network by Ghada Aldabbagh, Daniyal M. Alghazzawi, Syed Hamid Hasan, Mohammed Alhaddad, Areej Malibari, Li Cheng

“…Therefore, being motivated by the problems mentioned above, this paper proposes the concept of adaptive optimization-based neural network (AONN). The learning behavior and browsing behavior features are extracted and incorporated into the input of artificial neural network (ANN). …”
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Convolutional neural network (CNN) configuration using a learning automaton model for neonatal brain image segmentation. by Iran Sarafraz, Hamed Agahi, Azar Mahmoodzadeh

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In search of a warning strategy against exchange-rate attacks: Forecasting tactics using artificial neural networks by A. S. Andreou, G. A. Zombanakis, E. F. Georgopoulos, S. D. Likothanassis

Subjects: “…Shocks; Interest-rate; Forecasting; Neural-networks; Genetic algorithms.…”
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Global existence of periodic solutions in a simplified four-neuron BAM neural network model with multiple delays

“…<p>We consider a simplified bidirectional associated memory (BAM) neural network model with four neurons and multiple time delays. …”
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Advanced in Islanding Detection and Fault Classification for Grid-Connected Distributed Generation using Deep Learning Neural Network by Rusvaira Qatrunnada, Novizon Novizon, Mardini Hasanah, Tuti Angraini, Anton Anton

“…The use of an Artificial Neural Network (ANN) based on the learning vector quantization (LVQ) technique is proposed in this paper for fault classification and islanding detection in grid-connected distributed generators. …”
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Parallel convolutional neural network and empirical mode decomposition for high accuracy in motor imagery EEG signal classification. by Jaipriya D, Sriharipriya K C

“…In this work, we propose a novel method that addresses these challenges by employing empirical mode decomposition (EMD) for feature extraction and a parallel convolutional neural network (PCNN) for feature classification. This approach aims to mitigate non-stationary issues, improve performance speed, and enhance classification accuracy. …”
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Damage Identification of a Steel Frame Based on Integration of Time Series and Neural Network under Varying Temperatures by Minshui Huang, Wei Zhao, Jianfeng Gu, Yongzhi Lei

“…This study presents a methodology incorporating the autoregressive (AR) time series model with two-step artificial neural networks (ANNs) to identify damage under temperature variations. …”
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Modified AlexNet Convolution Neural Network For Covid-19 Detection Using Chest X-ray Images by Shadman Q. Salih, Hawre Kh. Abdulla, Zanear Sh. Ahmed, Nigar M. Shafiq Surameery, Rasper Dh. Rashid

“…In this work we used a deep learning technique based on Convolution Neural Network (CNN) to detect and diagnose COVID-19 disease using Chest X-ray images.  …”
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Analysis of reservoir rock permeability changes due to solid precipitation during waterflooding using artificial neural network by Azizollah Khormali, Soroush Ahmadi, Aleksandr Nikolaevich Aleksandrov

“…Experimental rock permeability data were then used to develop a model using a multi-layer perceptron (MLP) artificial neural network (ANN). In order to create a high-performing MLP-ANN model, various transfer functions and training algorithms were evaluated. …”
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A combined method of formation of a cryptographic key with secret modification of the results of synchronization of artificial neural networks by M. L. Radziukevich

Subjects: “…synchronized artificial neural networks…”
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Design of Morlet Wavelet Neural Networks for Solving the Nonlinear Van der Pol–Mathieu–Duffing Oscillator Model by Ali Hasan Ali, Muhammad Amir, Jamshaid Ul Rahman, Ali Raza, Ghassan Ezzulddin Arif

Subjects: “…Morlet wavelet neural network…”
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Anti-Periodic Dynamics of Quaternion-Valued Fuzzy Cellular Neural Networks with Time-Varying Delays on Time Scales by Shiping Shen, Bing Li, Yongkun Li

“…A class of quaternion-valued fuzzy cellular neural networks with time-varying delays on time scales is proposed. …”
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Predicting Shear Strength in FRP-Reinforced Concrete Beams Using Bat Algorithm-Based Artificial Neural Network by Mohammad Nikoo, Babak Aminnejad, Alireza Lork

“…The structure of the artificial neural network (ANN) is also optimized using the bat algorithm. …”
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Predicting the Number of COVID-19 Sufferers in Malang City Using the Backpropagation Neural Network with the Fletcher–Reeves Method by Syaiful Anam, Mochamad Hakim Akbar Assidiq Maulana, Noor Hidayat, Indah Yanti, Zuraidah Fitriah, Dwi Mifta Mahanani

“…Based on this hypothesis, this paper proposes a prediction model for the number of COVID-19 sufferers in Malang using the Backpropagation neural network with the Fletcher–Reeves method. The experimental results show that the Backpropagation neural network with the Fletcher–Reeves method has a better performance than the Backpropagation neural network with the gradient descent method. …”
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Efficient Hardware Implementation of a Multi-Layer Gradient-Free Online-Trainable Spiking Neural Network on FPGA by Ali Mehrabi, Yeshwanth Bethi, Andre van Schaik, Andrew Wabnitz, Saeed Afshar

Subjects: “…Spiking neural networks…”
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Convolutional neural networks for sea surface data assimilation in operational ocean models: test case in the Gulf of Mexico by O. Zavala-Romero, O. Zavala-Romero, A. Bozec, E. P. Chassignet, J. R. Miranda, J. R. Miranda

“…This work explores the application of convolutional neural networks (CNNs) in data assimilation within the context of the HYbrid Coordinate Ocean Model (HYCOM) in the Gulf of Mexico. …”
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The influence of big data, content marketing, and artificial neural networks on purchase decisions: the moderating role of purchase intentions by Sudarsono Sudarsono, Azis Rachman

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General Six-Step Discrete-Time Zhang Neural Network for Time-Varying Tensor Absolute Value Equations by Min Sun, Jing Liu

“…This article presents a general six-step discrete-time Zhang neural network (ZNN) for time-varying tensor absolute value equations. …”
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A Hybrid Approach by Integrating Brain Storm Optimization Algorithm with Grey Neural Network for Stock Index Forecasting by Yanqiu Sun

“…This paper aims to develop a novel hybrid stock index forecasting model named BSO-GNN based on the brain storm optimization (BSO) approach and the grey neural network (GNN) model by taking full advantage of the grey model in dealing with data with small samples and the neural network in handling nonlinear fitting problems. …”
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Prediction of COD Degradation in Fenton Oxidation Treatment of Kitchen Anaerobic Wastewater Based on IPSO-BP Neural Network by Tianpeng Zhang, Pengfei Ji, Dayong Tian, Rui Xu

“…The improved particle swarm optimization (IPSO) algorithm is used to optimize the back propagation (BP) neural network, and a prediction model of COD degradation is established based on IPSO-BP neural network. …”
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