Stability Analysis for Uncertain Neural Networks of Neutral Type with Time-Varying Delay in the Leakage Term and Distributed Delay by Qi Zhou, Xueying Shao, Jin Zhu, Hamid Reza Karimi

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Application of the Artificial Neural Network and Support Vector Machines in Forest Fire Prediction in the Guangxi Autonomous Region, China by Yudong Li, Zhongke Feng, Shilin Chen, Ziyu Zhao, Fengge Wang

“…They used feature selection and backpropagation neural networks and radial basis SVM to build forest fire prediction models. …”
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Multi-modal denoised data-driven milling chatter detection using an optimized hybrid neural network architecture by Haining Gao, Haoyu Wang, Hongdan Shen, Shule Xing, Yong Yang, Yinlin Wang, Wenfu Liu, Lei Yu, Mazhar Ali, Imran Ali Khan

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Finite-Time Stability Criteria for a Class of High-Order Fractional Cohen–Grossberg Neural Networks with Delay by Zhanying Yang, Jie Zhang, Junhao Hu, Jun Mei

“…This paper focuses on a class of delayed fractional Cohen–Grossberg neural networks with the fractional order between 1 and 2. …”
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Optimization Analysis Method of New Orthotropic Steel Deck Based on Backpropagation Neural Network-Simulated Annealing Algorithm by Xiuli Xu, Kewei Shi, Xuehong Li, Zhijun Li, Rengui Wang, Yuwen Chen

“…To study the effects of the fatigue performance due to the major design parameter of the orthotropic steel deck and to obtain a better design parameter, a construction parameter optimization method based on a backpropagation neural network (BPNN) and simulated annealing (SA) algorithm was proposed. …”
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A New Processing Method Combined with BP Neural Network for Francis Turbine Synthetic Characteristic Curve Research by Junyi Li, Canfeng Han, Fei Yu

“…A BP (backpropagation) neural network method is employed to solve the problems existing in the synthetic characteristic curve processing of hydroturbine at present that most studies are only concerned with data in the high efficiency and large guide vane opening area, which can hardly meet the research requirements of transition process especially in large fluctuation situation. …”
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An efficient artificial neural network-based optimization techniques for the early prediction of coronary heart disease: comprehensive analysis by Subhash Mondal, Ranjan Maity, Amitava Nag

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Enhancing Driving Safety and Environmental Consciousness through Automated Road Sign Recognition Using Convolutional Neural Networks by M. H. F. Md Fauadi, M. F. H. Mohd Zan, M. A. M Ali, L. Abdullah, S. N. Yaakop and A. Z. M. Noor

Subjects: “…traffic sign recognition, convolutional neural network, yolov3 network, environmental consciousness…”
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Neural network for step anomaly detection in head motion during fMRI using meta-learning adaptation by N.S. Davydov, V.V. Evdokimova, P.G. Serafimovich, V.I. Protsenko, A.G. Khramov, A.V. Nikonorov

Subjects: “…recurrent neural networks…”
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Methodology for Developing Hydrological Models Based on an Artificial Neural Network to Establish an Early Warning System in Small Catchments by Ivana Sušanj, Nevenka Ožanić, Ivan Marović

“…The aim and objective of this paper are to investigate the possibility of implementing an EWS in a small-scale catchment and to develop a methodology for developing a hydrological prediction model based on an artificial neural network (ANN) as an essential part of the EWS. …”
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Battery State of Charge and State of Health Estimation Using a New Hybrid Deep Neural Network Approach by Saeid Jorkesh, Ryan Ahmed, Saeid Habibi, Reza Hosseininejad, Siyuan Xu

“…This paper investigates various state of charge (SOC) and state of health (SOH) estimation methods, presenting a novel hybrid neural network that combines Gate Recurrent Unit (GRU) and Long Short-Term Memory (LSTM) models. …”
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A Methodology for Calculating Greenhouse Effect of Aircraft Cruise Using Genetic Algorithm-Optimized Wavelet Neural Network by Yong Tian, Lina Ma, Songtao Yang, Qian Wang

“…With respect to both cruise strategies and wind factors, a genetic algorithm-optimized wavelet neural network topology is designed to model the fuel flow-rate and developed using the real flight records data. …”
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Monte Carlo Noise Reduction Algorithm Based on Deep Neural Network in Efficient Indoor Scene Rendering System by Xiwen Chen, Jianfei Shen

“…For this problem, we propose a Monte Carlo noise reduction algorithm based on deep neural networks and apply it to the efficient rendering of an indoor scene. …”
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Sentiment Analysis Twitter Bahasa Indonesia Berbasis WORD2VEC Menggunakan Deep Convolutional Neural Network by Hans Juwiantho, Esther Irawati Setiawan, Joan Santoso, Mauridhi Hery Purnomo

“…Hasil percobaan yang telah dilakukan dengan algoritme Deep Convolutional Neural Network memiliki nilai akurasi terbaik sebesar 76,40%.   …”
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Performance of artificial neural networks and traditional methods in determining selected growth parameters of Alburnus sellal Heckel, 1843 by Ozcan Ebru Ifakat

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Prediction of Cutting Conditions in Turning AZ61 and Parameters Optimization Using Regression Analysis and Artificial Neural Network by Nabeel H. Alharthi, Sedat Bingol, Adel T. Abbas, Adham E. Ragab, Mohamed F. Aly, Hamad F. Alharbi

“…In this paper, an artificial neural network (ANN) modeling is used to estimate and optimize the surface roughness (Ra) value in cutting conditions of AZ61 magnesium alloy. …”
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GNN-EADD: Graph Neural Network-Based E-Commerce Anomaly Detection via Dual-Stage Learning by Zhouhang Shao, Xuran Wang, Enkai Ji, Shiyang Chen, Jin Wang

Subjects: “…Graph neural networks…”
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A Gray-Box Equivalent Neural Network Circuit Small-Signal Modeling Applied to GaN Transistors by Anwar Jarndal

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Optimasi Convolutional Neural Network Untuk Deteksi Covid-19 pada X-ray Thorax Berbasis Dropout by I Gede Totok Suryawan, I Putu Agus Eka Darma Udayana

“…Salah satunya dengan menggunakan Deep learning yaitu Convolutional Neural Network (CNN) yang sudah terbukti merupakan salah satu metode yang dapat digunakan untuk melakukan skrining pasien dan mendeteksi COVID-19. …”
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Adaptive Neural Network Control of a Class of Fractional Order Uncertain Nonlinear MIMO Systems with Input Constraints by Changhui Wang, Mei Liang, Yongsheng Chai

“…Combined with backstepping and adaptive technique, the unknown nonlinear uncertainties are approximated by the radial basis function neural network (RBF NN) in each step of the backstepping procedure. …”
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