Sparse connectivity enables efficient information processing in cortex-like artificial neural networks by Rieke Fruengel, Rieke Fruengel, Marcel Oberlaender, Marcel Oberlaender

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Evolutionary learning in neural networks by heterosynaptic plasticity by Zedong Bi, Ruiqi Fu, Guozhang Chen, Dongping Yang, Yu Zhou, Liang Tian

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Integrated neural network framework for multi-object detection and recognition using UAV imagery by Mohammed Alshehri, Tingting Xue, Tingting Xue, Ghulam Mujtaba, Yahya AlQahtani, Nouf Abdullah Almujally, Ahmad Jalal, Ahmad Jalal, Hui Liu, Hui Liu, Hui Liu

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Performance of functionalized CNT membranes for desalination - Parametric effects and Artificial neural network modelling by Deepa Durairaj, Santhosh Paramasivam, Natarajan Rajamohan, Manivasagan Rajasimman, Ragothaman M. Yennamalli, Roberto Baccoli, Gianluca Gatto

“…Among the two isotherms, Langmuir isotherm fitted the experimental data better than the Freundlich equation. An Artificial Neural Network (ANN) model was used to predict the behaviour of the membranes under different conditions. …”
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Determination of vibration characteristic in automatic tapping operations based on artificial neural networks by Emir Esim, Muhammed Demirel

“…Unpredictable vibrations significantly affect threading accuracy, reducing precision and shortening tool life. This study investigates the prediction of vibration characteristics during automatic tapping operations using artificial neural networks (ANN). …”
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Sinusoidal Neural Networks: Towards ANN that Learns Faster by Tekin Evrim Ozmermer

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Does neural computation feel like something? by Albert Gidon, Jaan Aru, Matthew E. Larkum, Matthew E. Larkum

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Human Brain Inspired Artificial Intelligence Neural Networks by Paschalis Theotokis

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Application of Artificial Neural Network(s) in Predicting Formwork Labour Productivity by Sasan Golnaraghi, Zahra Zangenehmadar, Osama Moselhi, Sabah Alkass

“…Artificial Neural Network (ANN) techniques that use supervised learning algorithms have proved to be more useful than statistical regression techniques considering factors like modeling ease and prediction accuracy. …”
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Prediction of dust storm using artificial neural networks in Kermanshah by Toba Alizadeheh, Majid rezaie banafsh, Gholamreza Goodarzi, Hashem Rostamzadeh

“…First, the dust data were normalized, and then Artificial Neural Network (ANN) models were used to predict dust concentration, while the Adaptive Neuro-Fuzzy Inference System (ANFIS) was employed to analyze and predict the time series of dust occurrence in MATLAB software. …”
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Is human-like decision making explainable? Towards an explainable artificial intelligence for autonomous vehicles by Jiming Xie, Yan Zhang, Yaqin Qin, Bijun Wang, Shuai Dong, Ke Li, Yulan Xia

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Cat Swarm Optimization Based Functional Link Artificial Neural Network Filter for Gaussian Noise Removal from Computed Tomography Images by M. Kumar, S. K. Mishra, S. S. Sahu

“…This paper proposes an evolutionary nonlinear adaptive filter approach, using Cat Swarm Functional Link Artificial Neural Network (CS-FLANN) to remove the unwanted noise. …”
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A comparative artificial neural networks for Schwarzschild black hole (SBH) radius by Khalil Ur Rehman, Wasfi Shatanawi, Weam G. Alharbi

“…The present work offers artificial neural networks assistance in the context of a choice of training functions for the prediction of astrophysical phenomena like the event horizon and radius of black holes. …”
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Comparison of Univariate and Multivariate Applications of GBLUP and Artificial Neural Network for Genomic Prediction of Growth and Carcass Traits in the Brangus Heifer Population by Sunday O. Peters, Kadir Kızılkaya, Mahmut Sinecen, Milt G. Thomas

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Chess Position Evaluation Using Radial Basis Function Neural Networks by Dimitrios Kagkas, Despina Karamichailidou, Alex Alexandridis

“…The proposed approach introduces models based on the radial basis function (RBF) neural network architecture trained with the fuzzy means algorithm, in conjunction with a novel set of input features; different methods of network training are also examined and compared, involving the multilayer perceptron (MLP) and convolutional neural network (CNN) architectures and a different set of input features. …”
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Classical machine learning and artificial neural network (ANN) to predict rejection in weaving industry by Toufique Ahmed

“…Interestingly, traditional machine learning models achieved more than 95% accuracy without any data preprocessing. In contrast, artificial neural networks (ANN) require data preprocessing to achieve high accuracy rates. …”
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Modeling Dual-Task Performance: Identifying Key Predictors Using Artificial Neural Networks by Arash Mohammadzadeh Gonabadi, Farahnaz Fallahtafti, Judith Heselton, Sara A. Myers, Ka-Chun Siu, Julie Blaskewicz Boron

“…Dual-task paradigms that combine cognitive and motor tasks offer a valuable lens for detecting subtle impairments in cognitive and physical functioning, especially in older adults. This study used artificial neural network (ANN) modeling to predict clinical, cognitive, and psychosocial outcomes from integrated gait, speech-linguistic, demographic, physiological, and psychological data collected during single- and dual-task conditions. …”
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Microstrip Patch Antenna Design Using a Four-Layer Feed Forward Artificial Neural Network Trained by Levenberg-Marquardt Algorithm by Jitu Prakash Dhar, Maodudul Hasan, Eisuke Nishiyama, Ichihiko Toyoda

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A comparative study of forecasting methods using real-life econometric series data by Cláudia Eliane da Matta, Natália Maria Puggina Bianchesi, Milena Silva de Oliveira, Pedro Paulo Balestrassi, Fabiano Leal

“…Abstract Paper aims This paper presents a comparative evaluation of different forecasting methods using two artificial neural networks (Multilayer Perceptron network and Radial Basis Functions Neural Network) and the Gaussian process regression. …”
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Performance evaluation, prediction analysis and optimization of experimental ORC using artificial neural networks (ANN) by Diki Ismail Permana, Federico Fagioli, Maurizio De Lucia, Dani Rusirawan, Istvan Farkas

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