Application of Artificial Neural Networks and Adaptive Neuro-Fuzzy Inference Systems to Predict Activated Carbon Properties for Methane Storage by Ali Ahmadpour, Neda Jahanshahi, Sajjad Rashidi, Naser Chenarani, Mohammad Jaber Darabi Mahboub

“…Two models of artificial neural networks and adaptive neuro-fuzzy interference systems are used. …”
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Applying a Cerebellar Model Articulation Controller Neural Network to a Photovoltaic Power Generation System Fault Diagnosis by Kuei-Hsiang Chao, Bo-Jyun Liao, Chin-Pao Hung

“…This study employed a cerebellar model articulation controller (CMAC) neural network to conduct fault diagnoses on photovoltaic power generation systems. …”
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Compound Fault Diagnosis for Gearbox Based Using of Euclidean Matrix Sample Entropy and One-Dimensional Convolutional Neural Network by Decai Zhang, Xueping Ren, Hanyue Zuo

“…In this paper, a one-dimensional convolutional neural network (1-D CNN) intelligent diagnosis method with improved SoftMax function is proposed. …”
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A Synergy of Convolutional Neural Networks for Sensor-Based EEG Brain–Computer Interfaces to Enhance Motor Imagery Classification by Souheyl Mallat, Emna Hkiri, Abdullah M. Albarrak, Borhen Louhichi

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Automatic Detection of Railway Faults Using Neural Networks: A Comparative Study of Transfer Learning Models and YOLOv11 by Omar Rodríguez-Abreo, Mario A. Quiroz-Juárez, Idalberto Macías-Socarras, Juvenal Rodríguez-Reséndiz, Juan M. Camacho-Pérez, Gabriel Carcedo-Rodríguez, Enrique Camacho-Pérez

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Existence and Exponential Stability of Equilibrium Point for Fuzzy BAM Neural Networks with Infinitely Distributed Delays and Impulses on Time Scales by Yongkun Li, Lijie Sun, Li Yang

“…By using the fixed point theorem and constructing a Lyapunov functional, we establish some sufficient conditions on the existence, uniqueness, and exponential stability of equilibrium point for a class of fuzzy BAM neural networks with infinitely distributed delays and impulses on time scales. …”
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Optimal adjustment of deep neural network parameters in estimating lost vital sign data in body wireless sensor networks by Aboulfazl Ebrahimi, Mahboubeh Shamsi, Morteza Mohajjel

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How to Identify Patterns of Citywide Dynamic Traffic at a Low Cost? An In-Depth Neural Network Approach with Digital Maps by Li Zhang, Ke Gong, Maozeng Xu, Aixing Li, Yuanxiang Dong, Yong Wang

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Artificial Neural Networks Model for Photosynthetic Rate Prediction of Leaf Vegetable Crops under Normal and Nutrient-Stressed in Greenhouse by Yohanes Bayu Suharto, Herry Suhardiyanto, Anas Dinurroman Susila, Supriyanto

“…This research focused on assessing the impact of nutrient stress on the photosynthetic rate in leaf vegetable crops and aimed to create a model using artificial neural networks (ANN) to predict photosynthetic rates under nutrient-stress conditions. …”
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M&A Short-Term Performance Based on Elman Neural Network Model: Evidence from 2006 to 2019 in China by Ming Xiao, Xionghui Yang, Ge Li

“…After comparing the five abnormal return (AR) calculation models, it is found that the commonly used market model method and the market adjustment method have statistical defects while the Elman feedback neural network model is capable of good nonlinear prediction ability. …”
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Acute ischemic stroke lesion segmentation in non-contrast CT images using 3D convolutional neural networks by A.V. Dobshik, S.K. Verbitskiy, I.A. Pestunov, K.M. Sherman, Yu.N. Sinyavskiy, A.A. Tulupov, V.B. Berikov

“…Our deep-learning approach is based on the popular 3D U-Net convolutional neural network architecture, which was modified by adding the squeeze-and-excitation blocks and residual connections. …”
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A New Type of Eye Movement Model Based on Recurrent Neural Networks for Simulating the Gaze Behavior of Human Reading by Xiaoming Wang, Xinbo Zhao, Jinchang Ren

“…In contrast to conventional psychology-based eye movement models, ours is based on a recurrent neural network (RNN) to generate a gaze point prediction sequence, by using the combination of convolutional neural networks (CNN), bidirectional long short-term memory networks (LSTM), and conditional random fields (CRF). …”
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Multi-scale feature fusion of deep convolutional neural networks on cancerous tumor detection and classification using biomedical images by U. M. Prakash, S. Iniyan, Ashit Kumar Dutta, Shtwai Alsubai, Janjhyam Venkata Naga Ramesh, Sachi Nandan Mohanty, Khasim Vali Dudekula

Subjects: “…Deep convolutional neural network…”
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Adaptive Output Feedback Control for the Trajectory Tracking of High-Speed Trains with Disturbance Uncertainties on the Basis of Neural Network Observers by Yang Liu, Weidong Li

“…Another neural network model is used to approximate the model uncertainties. …”
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Spatial Modeling of Airborne Particles (PM2.5 and PM10) in Tehran city Using Convolutional Neural Network. by Abed Bashar Doost, Mohammad Saadi Mesgari

“…This study presents an approach for air quality management in Tehran using the Convolutional Neural Network (CNN) algorithm. The proposed method provides the possibility of spatial modeling and preparation of risk maps of two important air pollutants, namely particulate matter 2.5 (PM2.5) and particulate matter 10 (PM10). …”
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Stabilization to Exponential Input-to-State Stability of a Class of Neural Networks with Delay by Observer-Based Aperiodic Intermittent Control by Mengyue Li, Biwen Li, Yuan Wan

“…Compared with the general neural networks, the state of the neural network investigated is not yet fully available. …”
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Parametric Estimation of Directional Wave Spectra from Moored FPSO Motion Data Using Optimized Artificial Neural Networks by Do-Soo Kwon, Sung-Jae Kim, Chungkuk Jin, MooHyun Kim

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Deep Learning Image Classification Rontgen Dada pada Kasus Covid-19 Menggunakan Algoritma Convolutional Neural Network by Leni Anggraini Susanti, Agus Mohamad Soleh, Bagus Sartono

“… Penelitian ini mengusulkan penggunaan Convolutional Neural Network (CNN) dengan arsitektur VGGNet-19 dan ResNet-50 untuk diagnosis COVID-19 melalui analisis citra rontgen dada. …”
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The Prediction of Metro Shield Construction Cost Based on a Backpropagation Neural Network Improved by Quantum Particle Swarm Optimization by Lanjun Liu, Denghui Liu, Han Wu, Xinyu Wang

“…The rough set theory was used to simplify the system of influencing factors to extract the dominant influencing factors and reduce the number of input variables in the BP neural network. Since the BP neural network easily falls into a local minimum and has a slow convergence speed, QPSO was used to optimize the weights and thresholds of the BP neural network. …”
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Trust as a key element in family mediation during divorce: strategies, practices (supervision experience with the use of neural networks) by V. V. Krivopuskov, I. V. Mkrtumova, O. E. Gracheva

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