Milling Machine Fault Diagnosis Using Acoustic Emission and Hybrid Deep Learning with Feature Optimization by Muhammad Umar, Muhammad Farooq Siddique, Niamat Ullah, Jong-Myon Kim

“…This paper presents a fault diagnosis technique for milling machines based on acoustic emission (AE) signals and a hybrid deep learning model optimized with a genetic algorithm. …”
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Knowledge graph-based intelligent control systems for real-time machine tool optimization by Hailong YANG, Jun YAO, Baorui DU

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A study on the application of the latent dirichlet allocation model in production optimization by Youbin Chen, Da Huang, Lifei Wang

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Correlation of rivaroxaban solubility in mixed solvents for optimization of solubility using machine learning analysis and validation by Muteb Alanazi, Jowaher Alanazi, Tareq Nafea Alharby, Bader Huwaimel

“…To complement experimental insights, machine learning models were employed to predict rivaroxaban solubility based on temperature, solvent type, and mass fraction of dichloromethane. …”
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Improving COPD Readmission Prediction with Optimized Machine Learning by Rajasekaran S, Shaik Mastan Val

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Analysis of drug crystallization by evaluation of pharmaceutical solubility in various solvents by optimization of artificial intelligence models by Wael A. Mahdi, Adel Alhowyan, Ahmad J. Obaidullah

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Parameter Self-tuning of Machine Side PI Controller in Wind Power System Based on Particle Swarm Optimization by ZHENG Liang, ZHANG Xizheng, LIU Zhihua, SHU Conghui, LU Zhangyu

“…In the machine side simulation model of wind power generation system based on PMSG, PI controller is often used for double-closed-loop control of speed and current. …”
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Modeling of Bayesian machine learning with sparrow search algorithm for cyberattack detection in IIoT environment by Faten Khalid Karim, José Varela-Aldás, Mohamad Khairi Ishak, Ayman Aljarbouh, Samih M. Mostafa

“…The BMLSSA-CAD technique uses the Bayesian Belief Network (BBN) model for cyberattack detection. The hyperparameter tuning process employs the sparrow search algorithm (SSA) model to enhance the BBN model performance. …”
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Advanced machine learning models for the prediction of ceramic tiles’ properties during the firing stage by V. Vasic, Milica, Awoyera, Paul O., Fadugba, Oladlu George, Barisic, Ivana, Nettinger Grubeša, Ivanka

“…This study employs advanced machine learning (ML) models to accurately predict these properties by capturing their complex nonlinear relationships. …”
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TMS: Ensemble Deep Learning Model for Accurate Classification of Monkeypox Lesions Based on Transformer Models with SVM by Elsaid Md. Abdelrahim, Hasan Hashim, El-Sayed Atlam, Radwa Ahmed Osman, Ibrahim Gad

“…Methods: This paper presents an ensemble model for classifying the monkeypox dataset, which includes transformer models and support vector machine (SVM). …”
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Multi-Objective Optimal Scheduling of Water Transmission and Distribution Channel Gate Groups Based on Machine Learning by Yiying Du, Chaoyue Zhang, Rong Wei, Li Cao, Tiantian Zhao, Wene Wang, Xiaotao Hu

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Optimizing ML models for cybercrime detection: balancing performance, energy consumption, and carbon footprint through multi-objective optimization by Romil Rawat

“…Abstract This study aims to enhance computational performance while minimizing environmental impact in AI (Artificial Intelligence) and ML (Machine Learning) applications, especially in cybersecurity, by developing energy-efficient models using a multi-objective optimization approach. …”
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Evaluation of Machine Learning and Ensemble Learning Models for Classification Using Delivery Data by İrem Karakaya

“…These results underscore the potential of such models to optimize logistics operations, reduce delays, and enhance customer satisfaction.Originality: This study demonstrates the effectiveness of machine and ensemble learning methods on complex logistics data, contributing to optimizing logistics efficiency and enhancing customer satisfaction. …”
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Explainable and Interpretable Model for the Early Detection of Brain Stroke Using Optimized Boosting Algorithms by Yogita Dubey, Yashraj Tarte, Nikhil Talatule, Khushal Damahe, Prachi Palsodkar, Punit Fulzele

“…The stroke pre-diction using optimized boosting machine learning algorithms is supported with explainable AI using LIME and SHAP. …”
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Advances in Virtual Power Plant Operations: A Review of Optimization Models by Fatemeh Marzbani, Ahmed H. Osman, Mohamed S. Hassan

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An explainable artificial intelligence model for predictive maintenance and spare parts optimization by Ufuk Dereci, Gülfem Tuzkaya

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CEEMDAN-IHO-SVM: A Machine Learning Research Model for Valve Leak Diagnosis by Ruixue Wang, Ning Zhao

“…Due to the slow convergence speed and the tendency to fall into local optimal solutions of the Hippopotamus Optimization Algorithm (HO), an improved Hippopotamus Optimization (IHO) algorithm-optimized Support Vector Machine (SVM) model for valve leakage diagnosis is introduced to further enhance the accuracy of valve leakage diagnosis. …”
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Optimizing HVAC&R System Efficiency and Comfort Levels Using Machine Learning-Based Control Methods by Suroor M. Dawood, Raad Z. Homod, Alireza Hatami

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Optimizing anticoagulant use for stroke prevention: a systematic review of machine learning interventions by Feras Almarshad, Abdurrahman Mohammad Alshahrani, Abdurrahman Saad Al Faiz, Aamir Abbas, Muhammad Shabbir

“…Objective: To identify and evaluate the use of machine learning interventions for optimizing anticoagulant use in stroke prevention among individuals at risk of stroke. …”
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Improving Search Query Accuracy for Specialized Websites Through Intelligent Text Correction and Reconstruction Models by Dana Simian, Marin-Eusebiu Șerban

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