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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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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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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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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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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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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Coordinate Transformation between Global and Local Datums Based on Artificial Neural Network with K-Fold Cross-Validation: A Case Study, Ghana by Yao Yevenyo Ziggah, Hu Youjian, Alfonso Rodrigo Tierra, Prosper Basommi Laari

“…The popularity of Artificial Neural Network (ANN) methodology has been growing in a wide variety of areas in geodesy and geospatial sciences. …”
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Artificial Neural Networks as Digital Twins for Whispering Gallery Mode Optical Sensors in Robotics Applications by Amir R. Ali, Mohamed W. A. Ramadan

“…Abstract This paper investigates the use of artificial neural networks (ANNs) as a viable digital twin or alternative to the typical whispering gallery mode (WGM) optical sensors in engineering systems, especially in dynamic environments like robotics. …”
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A novel committee machine and reviews of neural network and statistical models for currency exchange rate prediction: An experimental analysis by Trilok Nath Pandey, Alok Kumar Jagadev, Satchidananda Dehuri, Sung-Bae Cho

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COSMIC FP method in software development estimation using artificial neural networks based on orthogonal arrays by Nevena Rankovic, Dragica Rankovic, Mirjana Ivanovic, Ljubomir Lazic

“…This paper proposes a new, improved COmmon Software Measurement International Consortium function point (COSMIC FP) method that uses Artificial Neural Network (ANN) architectures based on Taguchi’s Orthogonal Array to estimate software development effort. …”
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Comprehensive deformation study in the new Austrian tunneling technique tunnel utilising artificial neural network model by Shubham Kanojiya, Gopal Krishna Mehta

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A review on amino acid based protein classification using supervised artificial intelligence (AI) models by Rida Zulfiqar, Talha Ahmed Khan, Abdullah Ayub Khan, Rubaika Akhtar, Sajid Ullah

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Transforming Neural Networks into Quantum-Cognitive Models: A Research Tutorial with Novel Applications by Milan Maksimovic, Ivan S. Maksymov

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Subtypes detection of papillary thyroid cancer from methylation assay via Deep Neural Network by Andrea Colacino, Andrea Soricelli, Michele Ceccarelli, Ornella Affinito, Monica Franzese

“…Results: By using RELU activation function and leaving out liquid tumors, our results show a remarkable performance of the neural network in classifying cancer and normal samples when applied to pan-cancer data (Validation AUC = 0.9903 and Validation Loss = 0.112). …”
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