Optimal Adaptive Modeling of Hydrogen Polymer Electrolyte Membrane Fuel Cells Based on Meta-Heuristic Algorithms Considering the Membrane Aging Factor by Mohamed Ahmed Ali, Mohey Eldin Mandour, Mohammed Elsayed Lotfy

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Machine Learning Approaches for Fault Detection in Internal Combustion Engines: A Review and Experimental Investigation by A. Srinivaas, N. R. Sakthivel, Binoy B. Nair

“…Additionally, this study incorporates advanced deep learning techniques, including a deep neural network (DNN), a one-dimensional convolutional neural network (1D-CNN), Transformer and a hybrid Transformer and DNN model which demonstrate superior performance in fault detection compared to traditional machine learning methods.…”
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Machine Learning Prediction of Mechanical Properties for Marine Coral Sand–Clay Mixtures Based on Triaxial Shear Testing by Bowen Yang, Kaiwei Xu, Zejin Wang, Haodong Sun, Peng Cui, Zhiming Chao

“…Utilizing this dataset, several predictive models were developed, including a standard Support Vector Machine (SVM), an SVM optimized via Genetic Algorithm (GA-SVM), an SVM enhanced by Particle Swarm Optimization (PSO-SVM), and a hybrid model incorporating Logical Development Algorithm preprocessing a SVM model (LDA-SVM). …”
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Data-Driven Insights into Concrete Flow and Strength: Advancing Smart Material Design Using Machine Learning Strategies by Muwaffaq Alqurashi

“…An experimental dataset with ten crucial input parameters was employed to develop and assess the models. While the GEP model demonstrated strong predictive capability (R² = 0.910 for CS and 0.882 for flow), the MEP model exhibited superior precision, attaining R² values of 0.951 for CS and 0.923 for flow. …”
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Automated Class Imbalance Learning via Few-Shot Multi-Objective Bayesian Optimization With Deep Kernel Gaussian Processes by Zhaoyang Wang, Shuo Wang, Damien Ernst, Chenguang Xiao

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Enhancing heart disease prediction with stacked ensemble and MCDM-based ranking: an optimized RST-ML approach by T. Ashika, G. Hannah Grace

“…IntroductionCardiovascular disease (CVD) is a leading global cause of death, necessitating the development of accurate diagnostic models. This study presents an Optimized Rough Set Theory-Machine Learning (RST-ML) framework that integrates Multi-Criteria Decision-Making (MCDM) for effective heart disease (HD) prediction. …”
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Highly Efficient JR Optimization Technique for Solving Prediction Problem of Soil Organic Carbon on Large Scale by Harsh Vazirani, Xiaofeng Wu, Anurag Srivastava, Debajyoti Dhar, Divyansh Pathak

“…Specifically, this study aims to (1) create an integrated dataset combining remote sensing and ground data for comprehensive SOC analysis, (2) develop a new optimization technique that enhances both machine learning and deep learning model performance, and (3) evaluate the algorithm’s efficiency and accuracy against established optimization methods like Jaya and GridSearchCV. …”
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An equipment behavioral study in fluidic production processes using data for an optimized predictive maintenance: Application to pneumatic valves in biopharmaceutical Industry by Wadel Florent, Tighazoui Ayoub, Houssin Remy, Coulibaly Amadou

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Optimizing mechanical properties of recycled aggregate concrete with graphene oxide and steel fibers: A predictive approach using ANN and RSM by S. Azhagarsamy, N. Pannirselvam

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Traffic flow modelling of vehicles on a six lane freeway: Comparative analysis of improved group method of data handling and artificial neural network model by Isaac Oyeyemi Olayode, Alessandro Severino, Frimpong Justice Alex, Elmira Jamei

“…This research presents a comparative analysis of two machine learning methodologies—Improved Group Method of Data Handling (GMDH) and Artificial Neural Network (ANN)—for modelling vehicular traffic flow on a six-lane freeway. …”
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Further Studies of Mechanical Damage on Machine-Harvested Cotton Fiber via Coupling Effect of Moisture Regains and Low Temperature by Jiqiang Cao, Lu Cheng, Limin Zhang, Xiang Liu, Hong Xu

“…Regression models for the relationship between temperature and mechanical properties under different moisture regain conditions were also established, showing good consistency. …”
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DNS over HTTPS Tunneling Detection System Based on Selected Features via Ant Colony Optimization by Hardi Sabah Talabani, Zrar Khalid Abdul, Hardi Mohammed Mohammed Saleh

“…Ant Colony Optimization (ACO) is integrated with machine learning algorithms such as XGBoost, K-Nearest Neighbors (KNN), Random Forest (RF), and Convolutional Neural Networks (CNNs) using CIRA-CIC-DoHBrw-2020 as the benchmark dataset. …”
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Comparing AI versus optimization workflows for simulation-based inference of spatial-stochastic systems by Michael Alexander Ramirez Sierra, Thomas R Sokolowski

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A Comparative Study of XBORE and XBOREOPT Hybrid Models for Ore Production Forecasting in the Mining Industry by Morris Mkokweza, Santhi Kumaran, George Mufungulwa

“…Few hybrid models have been developed to handle data from mine systems, and this study investigates the comparative performance of machine learning algorithms XBORE and XBOREOPT for predicting ore production in mining operations. …”
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An Approach to Finding a Robust Deep Learning Model by Alexey Boldyrev, Fedor Ratnikov, Andrey Shevelev

“…The rapid development of machine learning (ML) and artificial intelligence (AI) applications requires the training of a large numbers of models. …”
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Machine Learning-Based Surface Roughness Prediction in Turning of Hardened AISI 4340 Steels: Incorporating Tool Wear via Cutting Length by A. Ginting, M.S. Kasim, B.T. Hang Tuah Baharudin

“…This study explores the predictive modeling of surface roughness in the hard turning of AISI 4340 steel using machine learning techniques, specifically Random Forest (RF) and Gaussian Process Regression (GPR). …”
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Emotional Dynamics in Human–Machine Interactive Systems: Effectively Measuring Kuhn Poker Approach with Experimental Validation by Haoran Yang, Shu Liang

“…By systematically uncovering the causal mechanisms through which environmental factors regulate emotions and subsequently affect decision-making, this research provides critical theoretical and empirical insights for optimizing human–machine interaction design.…”
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Hybrid Deep Learning Models for Predicting Student Academic Performance by Kuburat Oyeranti Adefemi, Murimo Bethel Mutanga, Vikash Jugoo

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Structural Parameter Design of Magnetic Pulse Welding Coil for Dissimilar Metal Joints: Numerical Simulation, Parameter Optimization, and Experiments by Yangfan Qin, Changhui Ji, Hao Jiang, Yuefan Jiang, Junjia Cui, Guangyao Li

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Rapid screening and optimization of CO2 enhanced oil recovery operations in unconventional reservoirs: A case study by Shuqin Wen, Bing Wei, Junyu You, Yujiao He, Qihang Ye, Jun Lu

“…Based on the results of model interpretability, the genetic algorithm (GA) was coupled with RF (RF-GA model) to optimize the CO2-EOR process. …”
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