Eddy current modelling using multi-layer perceptron neural networks for detecting surface cracks by S. Harzallah, R. Rebhi, M. Chabaat, A. Rabehi

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Implementation of a Neural Network for Adaptive PID Tuning in a High-Temperature Thermal System by Juan Carlos Almachi, Ramiro Vicente, Edwin Bone, Jessica Montenegro, Edgar Cando, Salvatore Reina

“…This study proposes an adaptive control strategy combining a classical PID loop with real-time gain updates from a feed-forward artificial neural network (ANN). Implemented on an 18 kW retrofitted Blue-M furnace, the system was characterized by second-order transfer functions for heating and forced convection cooling. …”
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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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Review of Different Types of Neural Network Architectures by T. L. Makosso, A. Almaktoof, K. Abo-Al-Ez

“…Which leads to intelligent computational systems such as artificial neural networks. It is developed so that artificial neurons combined together would behave like a human brain. …”
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Data-driven diabetes mellitus prediction and management: a comparative evaluation of decision tree classifier and artificial neural network models along with statistical analysis by Idris Zubairu Sadiq, Babangida Sanusi Katsayal, Bashiru Ibrahim, Maryam Ibrahim, Hassan Aliyu Hassan, Umar Muhammad Ghali, Abdullahi Garba Usman, Abubakar Usman, Sani Isah Abba

“…This study compares the effectiveness of a Decision Tree Classifier and an Artificial Neural Network (ANN) in predicting Diabetes Mellitus. …”
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Harvesting Solar Energy: Prediction of Daily Global Horizontal Irradiance Using Artificial Neural Networks and Assessment of Electrical Energy of Photovoltaic at North Eastern Ethi... by Tegenu A. Woldegiyorgis, Abera D. Assamnew, Gezahegn A. Desalegn, Sentayehu Y. Mossie

“…Thus, the objectives of this article were: (i) assessing daily global horizontal irradiance using network types‐activation functions of artificial neural network (ANN); and (ii) evaluating the daily energy delivered to and available on photovoltaic (PV) cells of GaAs at Kemissie, Woldiya, and Hayk, in the northeastern part of Ethiopia. …”
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Computer graphics processing technology based on GIS model and its application by Quanpeng Ji

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AI post-intervention operational and functional outcomes prediction in ischemic stroke patients using MRIs by Emily Wittrup, John Reavey-Cantwell, Aditya S. Pandey, Dennis J. Rivet II, Kayvan Najarian

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Net2Brain: a toolbox to compare artificial vision models with human brain responses by Domenic Bersch, Domenic Bersch, Martina G. Vilas, Martina G. Vilas, Sari Saba-Sadiya, Timothy Schaumlöffel, Timothy Schaumlöffel, Kshitij Dwivedi, Christina Sartzetaki, Radoslaw M. Cichy, Radoslaw M. Cichy, Radoslaw M. Cichy, Gemma Roig, Gemma Roig

“…In cognitive neuroscience, the integration of deep neural networks (DNNs) with traditional neuroscientific analyses has significantly advanced our understanding of both biological neural processes and the functioning of DNNs. …”
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PHILOSOPHICAL AND ANTHROPOLOGICAL IMPORTANCE OF DEVELOPMENT OF ARTIFICIALLY CREATED INTELLIGENT SYSTEMS by Yu. D. Gensitskiy

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Analyzing analytical and software methods for deep foundation analysis and presenting a new solution for determining pile capacity using the PDA test by Ahmad Honarjoo, Vahed Ghiasi

“…In this system, the pile capacity for a chosen number of piles was finally determined by successfully combining a number of neural networks. The suggested system extends earlier neural networks for a comparable function and uses a self-organizing neural network for a set of data in training, testing, and valid datasets. …”
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Convolutional neural network approach for fault detection and characterization in medium voltage distribution networks by Atefeh Pour Shafei, J.Fernando A. Silva, J. Monteiro

“…Therefore, this paper introduces a novel method for detecting, classifying, and locating faults in power systems through voltage waveform analysis using a convolutional neural network (CNN) integrated with the Piecewise Function Put Together (PFPT) algorithm for fault detection and fault zone localization in a power distribution network. …”
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Integrating weighted gene co-expression network analysis and machine learning to elucidate neural characteristics in a mouse model of depression by Jinli Gao, Qinglang Wang, Jie Liu, Siqian Zheng, Jiahong Liu, Zhiyong Gao, Cheng Zhu

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Fused-MemBrain: a spiking processor combining CMOS and self-assembled memristive networks by Davide Cipollini, Hugh Greatorex, Michele Mastella, Elisabetta Chicca, Lambert Schomaker

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Elements of artificial intelligence in a predictive personalized model of pharmacotherapy choice in patients with heart failure with mildly reduced ejection fraction of ischemic or... by O. A. Osipova, A. V. Kontsevaya, V. V. Demko, E. V. Gosteva, A. A. Komisov, А. A. Kuzub, A. V. Serdyukova, A. S. Brizhaneva, R. N. Shepel, O. M. Drapkina

“…The result of this function is a parameter vector: AL, TNF-α, MMP-9, SI and quality of life (QOL). …”
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A hierarchical reinforcement learning approach for energy‐aware service function chain dynamic deployment in IoT by Shuyi Wang, Haotong Cao, Longxiang Yang

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Artificial Neural Network and response surface methodology modeling-based optimization approach for the ultrasonication-assisted extraction of phenolics from mustard (BARI Sharisa-... by Md. Waziur Rahman Chy, Tanvir Ahmed, Robin Sarkar, Md. Zohurul Islam, Md. Rahmatuzzaman Rana

“…Response Surface Methodology (RSM) and an Artificial Neural Network (ANN) multilayer perceptron model were employed to improve reliability, with hyperparameter tuning focused on the number of neurons and activation functions to prevent overfitting. …”
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An Innovative Artificial Intelligence Classification Model for Non-Ischemic Cardiomyopathy Utilizing Cardiac Biomechanics Derived from Magnetic Resonance Imaging by Liqiang Fu, Peifang Zhang, Liuquan Cheng, Peng Zhi, Jiayu Xu, Xiaolei Liu, Yang Zhang, Ziwen Xu, Kunlun He

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Bio-realistic and versatile artificial dendrites made of anti-ambipolar transistors by Yifei Yang, Mingkun Xu, Tianhang Zhang, Chenfei Miao, Juan Lyu, Jing Pei, Peng Li, Guoqi Li, Si Wu, Huanglong Li

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THE CURRENT STATE OF ARTIFICIAL INTELLIGENCE IN RADIOLOGY – A REVIEW OF THE BASIC CONCEPTS, APPLICATIONS, AND CHALLENGES by Mariana Yordanova

“…Deep learning, especially deep convolutional neural networks (CNNs), has become a prominent approach, mimicking brain functions to process images through multiple layers. …”
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