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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Autoencoder neural network-based abnormal data detection in edge computing enabled large-scale IoT systems by Tianqi YU, Yongxu ZHU, Xianbin WANG

Subjects: “…autoencoder neural network…”
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Study of emotion recognition based on fusion multi-modal bio-signal with SAE and LSTM recurrent neural network by You-jun LI, Jia-jin HUANG, Hai-yuan WANG, Ning ZHONG

Subjects: “…stacked auto-encoder neural network…”
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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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Combination of gray level features with deep transfer learning for copra classification using machine learning and neural networks by A. Stephen Sagayaraj, T. Kalavathi Devi

“…These concatenated features were evaluated using various machine learning classifiers and neural networks. Among the classifiers tested, Neural Network-based Pattern Recognition (NNPR) achieved the highest accuracy of 99.6%, sensitivity of 99.64%, specificity of 99.64%, F1-Score of 99.6, and a Kappa score of 0.99, demonstrating its superior performance. …”
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Aircraft Position Estimation Using Deep Convolutional Neural Networks for Low SNR (Signal-to-Noise Ratio) Values by Przemyslaw Mazurek, Wojciech Chlewicki

Subjects: “…deep convolutional neural networks…”
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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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Prediction of Dynamic Compressive Strength of Hydraulic Asphalt Concrete Based on BP Neural Network and Response Surface Fitting by XIN Zhenke

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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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Application of GA-BP Neural Network Optimized by Grey Verhulst Model around Settlement Prediction of Foundation Pit by C. Y. Liu, Y. Wang, X. M. Hu, Y. L. Han, X. P. Zhang, L. Z. Du

“…The predicted values of the BP neural network, GA-BP neural network, BP neural network optimized by the grey Verhulst model, and GA-BP neural network optimized by the grey Verhulst model are detailed compared with the measured values. …”
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