An Improved Ant Colony Optimization to Uncover Customer Characteristics for Churn Prediction by Ibrahim Al-Shourbaji, Abdoh Jabbari, Shaik Rizwan, Mostafa Mehanawi, Phiros Mansur, Mohammed Abdalraheem

“…Feature selection (FS) is an integral part in Machine Learning (ML) models which aims to improve performance and reduce computational time (CT). …”
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Lorenz-PSO Optimized Deep Neural Network for Enhanced Phonocardiogram Classification by Awais Mahmood, Mousa Alhajlah, Habib Dhahri, Abdulaziz Almaslukh

“…Despite deep learning’s popularity, dataset imbalance, signal feature repetition, and noise volatility hurt classification models. Two modifications of Lorenz chaotic system hybrid with PSO are given to improve optimal hyperparameter selection of deep learning architecture EfficientNet-To. …”
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Research on Multi-Objective Optimization Design of High-Speed Train Wheel Profile Based on RPSTC-GJO by Mao Li, Hao Ding, Meiqi Wang, Xingda Yang, Bin Kong

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Universal anomaly detection at the LHC: transforming optimal classifiers and the DDD method by Sascha Caron, José Enrique García Navarro, María Moreno Llácer, Polina Moskvitina, Mats Rovers, Adrián Rubio Jímenez, Roberto Ruiz de Austri, Zhongyi Zhang

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Optimization Design and Dynamic Characteristics Analysis of Self-Responsive Anti-Falling Device for Inclined Shaft TBMs by Han Peng, Can Yang, Linjian Shangguan, Lianhui Jia, Bing Li, Chuang Xu, Wenjuan Yang

“…Based on the operational conditions of the “Tianyue” tunnel boring machine, a three-dimensional model was constructed using SolidWorks. …”
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Integrating Energy and Time Efficiency in Robotic Manufacturing Cell Design: A Methodology for Optimizing Workplace Layout by Roman Ruzarovsky, Tibor Horak, Robert Bocak, Martin Csekei, Roman Zelník

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Predicting the outcome of psychological treatments for borderline personality disorder and posttraumatic stress disorder: a machine learning approach to predict long-term outcome o... by Jakob Blaß, Benjamin Iffland, Philipp Herzog, Tim Kaiser, Thomas Elbert, Carolin Steuwe

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Relay Placement for Maximum Flow Rate via Learning and Optimization Over Riemannian Manifolds by Imtiaz Nasim, Ahmed S. Ibrahim

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Short-Term Electric Load Forecasting for an Industrial Plant Using Machine Learning-Based Algorithms by Oğuzhan Timur, Halil Yaşar Üstünel

“…The integration of calendar, meteorological, and lagging electrical variables, along with machine learning-based algorithms, is employed to boost forecasting accuracy and optimize energy utilization. …”
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Estimating Energy Consumption During Soil Cultivation Using Geophysical Scanning and Machine Learning Methods by Jasper Tembeck Mbah, Katarzyna Pentoś, Krzysztof S. Pieczarka, Tomasz Wojciechowski

“…The aim of this study was to estimate energy consumption during soil cultivation using geophysical scanning data and machine learning (ML) algorithms. This included determining the optimal set of independent variables and the most suitable ML method. …”
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Innovative machine learning approaches for complexity in economic forecasting and SME growth: A comprehensive review by Mustafa I. Al-Karkhi, Grzegorz Rza̧dkowski

“…The findings underscore the transformative role of ML and XAI in economic forecasting and offer valuable guidance for researchers and decision-makers to optimize forecasting models for business growth and economic planning.…”
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Extraction of kaolin and tribo informative analysis of the Al-kaolin composite through machine learning approaches by V. S. S. Venkatesh, Guttikonda Manohar, Pandu Ranga Vundavilli, M. M. Mahapatra, Ashish Goyal, Abhijit Bhowmik

“…To further understand and predict the behaviour of the composites, a systematic dataset was collected, and various machine learning (ML) models were trained and tested for predictive modelling of wear rate and COF. …”
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Aspect-Based Sentiment Analysis for Afaan Oromoo Movie Reviews Using Machine Learning Techniques by Obsa Gelchu Horsa, Kula Kekeba Tune

“…The implementation result shows that the optimal values of models’ performance evaluation parameters were generated using different hyperparameter tuning settings.…”
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Sustainable Polyurethane-Based Polymer Concrete: Mechanical and Non-destructive Properties with Machine Learning Technique by S. I. Haruna, Han Zhu, Yasser E. Ibrahim, Jian Yang, AIB Farouk, Jianwen Shao, Musa Adamu, Omar Shabbir Ahmed

“…The experimental datasets from mechanical and NDT tests were utilized to train machine learning (ML) models, including multilinear regression (MLR), artificial neural network (ANN), support vector machine (SVM), Gaussian regression process (GPR), and stepwise regression (SWR) models for estimating the f c. …”
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Machine Learning Prediction of Foaming in Anaerobic Co-Digestion from Six Key Process Parameters by Sarah E. Daly, Ji-Qin Ni

“…Cu) associated with digester foaming. Among the tested machine learning models, the support vector machine (SVM) algorithm achieved the highest recognition accuracy of 87%. …”
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Power Transformer Prognostics and Health Management Using Machine Learning: A Review and Future Directions by Ryad Zemouri

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Assessing the association of multi-environmental chemical exposures on metabolic syndrome: A machine learning approach by Yehoon Jo, Mi-Yeon Shin, Sungkyoon Kim

“…This study used data from 2,960 participants in the Korean National Environmental Health Survey (KoNEHS) cycle 4 (2018–2020) to examine associations between environmental exposures and MetS risk through machine learning (ML) approaches. Eight ML algorithms were applied, with the multilayer perceptron (MLP) and random forest (RF) models identified as optimal predictors. …”
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Textual similarity for legal precedents discovery: Assessing the performance of machine learning techniques in an administrative court by Hugo Mentzingen, Nuno António, Fernando Bacao, Marcio Cunha

“…Our findings reveal that models focusing on granular text representations perform optimally, especially when extracting concepts and relations. …”
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Autoencoder Extreme Learning Machine for Fingerprint-Based Positioning: A Good Weight Initialization is Decisive by Darwin P. Quezada Gaibor, Lucie Klus, Roman Klus, Elena Simona Lohan, Jari Nurmi, Mikko Valkama, Joaquin Huerta, Joaquin Torres-Sospedra

“…Indoor positioning based on machine-learning (ML) models has attracted widespread interest in the last few years, given its high performance and usability. …”
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A machine learning approach for mapping susceptibility to land subsidence caused by ground water extraction by Diana Orlandi, Esteban Díaz, Roberto Tomás, Federico A. Galatolo, Mario G.C.A. Cimino, Carolina Pagli, Nicola Perilli

“…Then, additional Conditioning Factors (CFs) with increased spatial resolution were used to train several ML models and generate a new LSSI map. The Extra-Trees Classifier (ETC) outperformed the other approaches, achieving the best performance with a weighted average precision and F1-Score of 0.96, after optimizing its hyperparameters. …”
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