Binary Classification of Customer’s Online Purchasing Behavior Using Machine Learning by Ahmad Aldelemy, Raed A. Abd-Alhameed

“…Our methodology includes data analysis, transformation, training, and testing machine learning classifiers such as Naïve Bayes, Decision Trees, Random Forests, Support Vector Machines, Logistic Regression, Artificial Neural Networks, AdaBoost, and Gradient Descent. …”
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Assessing the influence of bibliometric factors and organizational characteristics on the centrality degree of inter-university collaborative networks: a neural network approach by Juan David Reyes-Gómez, Efrén Romero-Riaño

“…This study used artificial neural networks, particularly a multilayer perceptron. …”
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An Improved Direct Torque Control with an Advanced Broken-Bar Fault Diagnosis for Induction Motor Drives by Oualid Aissa, Abderrahim Reffas, Hicham Talhaoui, Djamel Ziane, Abdelhakim Saim

“…This paper presents an advanced strategy combining fuzzy logic and artificial neural networks (ANNs) for direct torque control (DTC) and broken-bar fault diagnosis in induction motors. …”
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3MT Competition (EUSIPCO2024): A peek into the black box: Insights into the functionality of complex-valued neural networks for multichannel speech enhancement by Annika Briegleb

“…Artificial neural networks (ANNs) have become an important part of signal processing research. …”
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Integrating AI and statistical methods for enhancing civil structures: current trends, practical issues and future direction by Asraar Anjum, Meftah Hrairi, Abdul Aabid, Maisarah Ali

“…This review systematically examines how advanced optimization techniques, including artificial neural networks (ANNs), Design of Experiments (DOE), and fuzzy logic (FL), are transforming civil engineering practices. …”
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Influence of proteinoids on calcium carbonate polymorphs precipitation in supersaturated solutions by Panagiotis Mougkogiannis, Andrew Adamatzky

“…We discuss the implications and applications of our work in the fields of bio-inspired computing, artificial neural networks, and origin of life research.…”
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Application of machine learning in fracture analysis of edge crack semi-infinite elastic plate by Saeed H. Moghtaderi, Alias Jedi, Ahmad Kamal Ariffin, Prakash Thamburaja

“…This paper discusses the application of machine learning techniques, notably artificial neural networks (ANN), in the fracture analysis of semi-infinite elastic plates with edge cracks. …”
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Discriminative training of spiking neural networks organised in columns for stream‐based biometric authentication by Enrique Argones Rúa, Tim Vanhamme, Davy Preuveneers, Wouter Joosen

“…One of the challenges when using SNNs is the discriminative training of the network since it is not straightforward to apply the well‐known error backpropagation (EBP), massively used in traditional artificial neural networks (ANNs). A network structure based on neuron columns is proposed, resembling cortical columns in the human cortex, and a new derivation of error backpropagation for the spiking neural networks that integrate the lateral inhibition in these structures. …”
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Modelling and optimization of well hole cleaning using artificial intelligence techniques by Nageswara Rao Lakkimsetty, Hassan Rashid Ali Al Araimi, G. Kavitha

“…This study aims to improve the accuracy and practicality of hole cleaning assessment by applying Artificial Intelligence (AI) techniques, specifically Artificial Neural Networks (ANN) and Genetic Algorithms (GA), to predict downhole parameters and optimize drilling processes. …”
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Modelling Laser Milling of Microcavities for the Manufacturing of DES with Ensembles by Pedro Santos, Daniel Teixidor, Jesus Maudes, Joaquim Ciurana

“…In total, 162 different conditions are tested in a process that is modeled with the following state-of-the-art data-mining regression techniques: Support Vector Regression, Ensembles, Artificial Neural Networks, Linear Regression, and Nearest Neighbor Regression. …”
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Integrating AI and statistical methods for enhancing civil structural practices: current trends, practical issues, and future direction by Asraar Anjum, Meftah Hrairi, Abdul Aabid Shaikh, Noorfazrina Yatim, Maisarah Ali

“…This review systematically examines how advanced optimization techniques, including artificial neural networks (ANNs), Design of Experiments (DOE), and fuzzy logic (FL), are transforming civil engineering practices. …”
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Intelligent model and optimization of ultrasound-assisted extraction of antioxidants and amylase enzyme from Gnaphalium affine D. Don by Naphatrapi Luangsakul, Kannika Kunyanee, Sandra Kusumawardani, Tai Van Ngo

“…The study involves two statistical methods: artificial neural networks (ANN) and response surface methodology (RSM) to model and optimize extraction procedure for improving the yield of antioxidant and amylase enzyme activity (AEA). …”
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Artificial intelligence based prediction and multi-objective RSM optimization of tectona grandis biodiesel with Elaeocarpus Ganitrus by V Vinoth Kannan, Bhavesh Kanabar, J Gowrishankar, Ali Khatibi., Sarfaraz Kamangar, Amir Ibrahim Ali Arabi, Pushparaj Thomai, Jasmina Lozanović

“…Advanced Machine Learning (ML) models, including Artificial Neural Networks (ANN), K-Nearest Neighbors (KNN), Extreme Gradient Boosting (XGB), and Random Trees (RT), were employed for predictive analysis, with ANN outperforming RSM in accuracy. …”
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Improved Set-point Tracking Control of an Unmanned Aerodynamic MIMO System Using Hybrid Neural Networks by Oduetse Matsebe, David Mohammed Ezekiel, Ravi Samikannu

“…Artificial neural networks (ANN), an Artificial Intelligence (AI) technique, are both bio-inspired and nature-inspired models that mimic the operations of the human brain and the central nervous system that is capable of learning. …”
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Research on 3D printing concrete mechanical properties prediction model based on machine learning by Yonghong Zhang, Suping Cui, Bohao Yang, Xinxin Wang, Tao Liu

“…Our study explores the fundamentals and practicality of several models, such as artificial neural networks, decision trees, random forests, support vector regression, and linear regression. …”
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SPICE-Level Demonstration of Unsupervised Learning With Spintronic Synapses in Spiking Neural Networks by Salah Daddinounou, Anteneh Gebregiorgis, Said Hamdioui, Elena-Ioana Vatajelu

“…Spiking Neural Networks (SNNs) are Artificial Neural Networks which promise to mimic the biological brain processing with unsupervised online learning capability for various cognitive tasks. …”
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Application of artificial intelligence for feature engineering in education sector and learning science by Chao Wang, Tao Li, Zhicui Lu, Zhenqiang Wang, Tmader Alballa, Somayah Abdualziz Alhabeeb, Maryam Sulaiman Albely, Hamiden Abd El-Wahed Khalifa

“…In order to tackle this issue, we utilized three sophisticated machine learning methodologies: Adaptive Lasso (ALasso), Artificial Neural Networks (ANN), and Support Vector Regression (SVR). …”
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Implications of Spatiotemporal Data Aggregation on Short-Term Traffic Prediction Using Machine Learning Algorithms by Rivindu Weerasekera, Mohan Sridharan, Prakash Ranjitkar

“…As a step towards addressing these problems, this paper investigates the ability of Artificial Neural Networks, Random Forests, and Support Vector Regression algorithms to reliably model traffic flow at different data resolutions and respond to unexpected traffic incidents. …”
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A New Decomposition Ensemble Learning Approach with Intelligent Optimization for PM2.5 Concentration Forecasting by Guangyuan Xing, Shaolong Sun, Jue Guo

“…According to the principle of “divide and conquer,” we propose a novel decomposition ensemble learning approach by integrating ensemble empirical mode decomposition (EEMD), artificial neural networks (ANNs), and adaptive particle swarm optimization (APSO) for forecasting PM2.5 concentrations. …”
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Design Space Approach in Optimization of Fluid Bed Granulation and Tablets Compression Process by Jelena Djuriš, Djordje Medarević, Marko Krstić, Ivana Vasiljević, Ivana Mašić, Svetlana Ibrić

“…Percent of paracetamol released and tablets hardness were determined as critical quality attributes. Artificial neural networks (ANNs) were applied in order to determine design space. …”
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