Layout Optimization of Two Autonomous Underwater Vehicles for Drag Reduction with a Combined CFD and Neural Network Method by Wenlong Tian, Zhaoyong Mao, Fuliang Zhao, Zhicao Zhao

“…Then, based on the CFD data, a back-propagation neural network (BPNN) method is used to describe the relationship between the layout parameters and the drag of the fleet. …”
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Synchronization of Chaotic Neural Networks with Leakage Delay and Mixed Time-Varying Delays via Sampled-Data Control by Ting Lei, Qiankun Song, Zhenjiang Zhao, Jianxi Yang

“…This paper investigates the synchronization problem for neural networks with leakage delay and both discrete and distributed time-varying delays under sampled-data control. …”
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A hybrid Framework for plant leaf disease detection and classification using convolutional neural networks and vision transformer by Sherihan Aboelenin, Foriaa Ahmed Elbasheer, Mohamed Meselhy Eltoukhy, Walaa M. El-Hady, Khalid M. Hosny

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Eigen Solution of Neural Networks and Its Application in Prediction and Analysis of Controller Parameters of Grinding Robot in Complex Environments by Shixi Tang, Jinan Gu, Keming Tang, Wei Ding, Zhengyang Shang

“…Firstly, this paper defined the conceptions of neural network solution, neural network eigen solution, neural network complete solution, and neural network partial solution and the conceptions of input environments, output environments, and macrostructure of neural networks. …”
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Finite-Time Nonfragile Dissipative Control for Discrete-Time Neural Networks with Markovian Jumps and Mixed Time-Delays by Ling Hou, Dongyan Chen, Chan He

“…This paper considers the stochastic finite-time dissipative (SFTD) control problem based on nonfragile controller for discrete-time neural networks (NNS) with Markovian jumps and mixed delays, in which the mode switching phenomenon, is described as Markov chain, and the mixed delays are composed of discrete time-varying delay and distributed delays. …”
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Prediction of mechanical behavior of epoxy polymer using Artificial Neural Networks (ANN) and Response Surface Methodology (RSM) by Khalissa Saada, Salah Amroune, Moussa Zaoui

“…Afterwards, the nonlinear functional relationship of input parameters between epoxy sample geometries and sections was established using the response surface model (RSM) and the artificial neural network (ANN) to predict the output parameters of mechanical properties (Young's Modulus and stress). …”
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Effectiveness of Different Artificial Neural Network Models in Establishing the Suitable Dosages of Coagulant and Chlorine in Water Treatment Works by Dnyaneshwar V. Wadkar, Ganesh C. Chikute, Pravin S. Patil, Pallavi D. Wadkar and Manasi G. Chikute

“…It has been found that radial basis function neural networks (RBFNN) and generalized regression neural networks (GRNN) modeling provide better prediction. …”
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Global exponential synchronization of discrete-time high-order BAM neural networks with multiple time-varying delays by Er-yong Cong, Li Zhu, Xian Zhang

Subjects: “…discrete-time high-order bam neural network…”
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Prediction of Punching Capacity of Slab-Column Connections without Transverse Reinforcement Based on a Backpropagation Neural Network by Jie Bu, FanZhen Zhang, Meng Zhu, Zhiyang He, Qigao Hu

“…Then, based on the Levenberg–Marquardt (LM) algorithm and using the nonlinear function of the backpropagation neural network (BPNN), a prediction model of the punching capacity of slab-column connections without transverse reinforcement is established. …”
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Graphon Neural Networks-Based Detection of False Data Injection Attacks in Dynamic Spatio-Temporal Power Systems by Rachad Atat, Abdulrahman Takiddin, Muhammad Ismail, Erchin Serpedin

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Hamiltonian Neural Network 6-DoF Rigid-Body Dynamic Modeling Based on Energy Variation Estimation by Fei Simiao, Huo Lin, Sun Zhixiao, Wang He, Lu Yuanjie, He Jile, Luo Qing, Su Qihang

“…This study introduces a novel deep modeling approach that utilizes Hamiltonian neural networks to address the challenges of modeling the six degrees of freedom rigid-body dynamics induced by control inputs in various domains such as aerospace, robotics, and automotive engineering. …”
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Intelligent Image Recognition System for Marine Fouling Using Softmax Transfer Learning and Deep Convolutional Neural Networks by C. S. Chin, JianTing Si, A. S. Clare, Maode Ma

“…The proposed system utilizes transfer learning and deep convolutional neural network (CNN) to perform image recognition on the fouling image by classifying the detected fouling species and the density of fouling on the surface. …”
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An Improved Fuzzy Neural Network Compound Control Scheme for Inertially Stabilized Platform for Aerial Remote Sensing Applications by Xiangyang Zhou, Yating Li, Yuan Jia, Libo Zhao

“…An improved fuzzy neural network (FNN)/proportion integration differentiation (PID) compound control scheme based on variable universe and back-propagation (BP) algorithms is proposed to improve the ability of disturbance rejection of a three-axis inertially stabilized platform (ISP) for aerial remote sensing applications. …”
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Artificial intelligence for biodiversity: Exploring the potential of recurrent neural networks in forecasting arthropod dynamics based on time series by Sébastien Lhoumeau, João Pinelo, Paulo A.V. Borges

“…This research conducted a comparative analysis of Local Polynomial Regression (LOESS), Seasonal Autoregressive Integrated Moving Average (SARIMA), and Recurrent Neural Network (RNN) models for time-series prediction. …”
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Pengaruh Dataset terhadap Performa Convolutional Neural Network pada Klasifikasi X-Ray Pasien Covid-19 by Chyntia Raras Ajeng Widiawati

“…Algoritma Convolutional Neural Network (CNN) adalah salah satu algoritma popular dengan performa yang sangat baik pada klasifikasi citra X-Ray pasien COVID-19. …”
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Developing a brain inspired multilobar neural networks architecture for rapidly and accurately estimating concrete compressive strength by Bashar Alibrahim, Ahed Habib, Maan Habib

Subjects: “…Artificial neural networks…”
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A BP Neural Network-Based GIS-Data-Driven Automated Valuation Framework for Benchmark Land Price by Lei Wu, Yu Zhang, Yongchang Wei, Fangyu Chen

“…In this paper, an effective data-driven automated valuation framework is proposed for valuing real estate assets by combining a GIS (geographic information system) and neural network technologies. This framework can automatically obtain the values of spatial factors affecting land price from GIS and generate training set data for training the neural network to identify the complex relationship between all kinds of factors and benchmark land prices. …”
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Exploration on Robustness of Exponentially Global Stability of Recurrent Neural Networks with Neutral Terms and Generalized Piecewise Constant Arguments by Wenxiao Si, Tao Xie, Biwen Li

“…With a view to the interference of piecewise constant arguments (PCAs) and neutral terms (NTs) to the original system and the significant applications in the signal transmission process, we explore the robustness of the exponentially global stability (EGS) of recurrent neural network (RNN) with PCAs and NTs (NPRNN). The following challenges arise: what the range of PCAs and the scope of NTs can NPRNN tolerate to be exponentially stable. …”
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Bayesian neural network modelling for estimating ecological footprints and blue economy sustainability across G20 nations by Muhammad Akhtar, Jian Xu, Umair Kashif, Kishwar Ali, Hafiz Muhammad Naveed, Muhammad Haris

“…The study applied Bayesian neural network (BNN), OLS, fixed effects, and a two-step generalized method of moments on the panel dataset of G20 countries over the period 2000 to 2021. …”
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LSTM Recurrent Neural Network-Based Frequency Control Enhancement of the Power System with Electric Vehicles and Demand Management by G. Sundararajan, P. Sivakumar

“…This research work investigates a deep learning strategy based on a long short-term memory recurrent neural network to identify active power fluctuations in real-time. …”
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