Machine Learning Methods for Forecasting Intermittent Tin Ore Production by Nabila Dhia Alifa Rahmah, Budhi Handoko, Anindya Apriliyanti Pravitasari

“…This study's findings show that a serial combination of the Random Forest classification method and CatBoost forecasting can produce accurate tin ore production forecasts for the selected CSD (RMSE = 0.271, MAE = 0.179, MAE = 0.730, F1-score = 0,80). …”
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Prediction of Concrete Compressive Strength and Slump by Machine Learning Methods by M. Timur Cihan

“…Machine learning methods have been successfully applied to many engineering disciplines. …”
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Censoring Sensitivity Analysis for Benchmarking Survival Machine Learning Methods by János Báskay, Tamás Mezei, Péter Banczerowski, Anna Horváth, Tamás Joó, Péter Pollner

“…We address this gap by introducing a systematic benchmarking methodology focused on censoring sensitivity. (2) Methods: We developed a benchmarking framework that assesses survival models through controlled modification of censoring conditions. …”
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Comparison of Machine Learning Methods for Menstrual Cycle Analysis and Prediction by Mutiara Khairunisa, Desak Made Sidantya Amanda Putri, I Gusti Ngurah Lanang Wijayakusuma

“…This study compares three machine learning methods—Long Short-Term Memory (LSTM), Convolutional Neural Network (CNN), and Decision Tree—for analyzing and predicting menstrual cycles. …”
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Modeling Soil Temperature with Fuzzy Logic and Supervised Learning Methods by Bilal Cemek, Yunus Kültürel, Emirhan Cemek, Erdem Küçüktopçu, Halis Simsek

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CNN and Transfer Learning methods for enhanced dermatological disease detection by Habibulla C. Venkataiah, T. Jayachandra Prasad, G. Gopinath, B. Charitha, G. Dharma Teja, B. Lomith Reddy

“…Our approach involved Transfer Learning with a pre-trained ResNet50 model to try to improve performance and efficiency using features learned from large-scale datasets. …”
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Desire to learn qualitative methods among researchers in healthcare fields by Warren Bareiss

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Comparison of Machine Learning Methods for Predicting Electrical Energy Consumption by Retno Wahyusari, Sunardi Sunardi, Abdul Fadlil

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Transfer learning methods for Three-Axis CNC anomaly detection by Eugene Li, Yang Li, Sasank Kakarla, William Melek, Sanjeev Bedi

“…Transfer learning is a machine learning method used to train a network using prior knowledge from a source network. …”
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Briefing in Application of Machine Learning Methods in Ion Channel Prediction by Hao Lin, Wei Chen

“…In this review, we will briefly introduce and discuss the recent progress in ion channel prediction using machine learning methods.…”
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Continual Learning With Neuromorphic Computing: Foundations, Methods, and Emerging Applications by Mishal Fatima Minhas, Rachmad Vidya Wicaksana Putra, Falah Awwad, Osman Hasan, Muhammad Shafique

“…The challenging deployment of compute- and memory-intensive methods from Deep Neural Network (DNN)-based Continual Learning (CL), underscores the critical need for a paradigm shift towards more efficient approaches. …”
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Springback Prediction of Sandwich Panel Using Machine Learning Methods by Raja Ouled Ahmed Ben Ali, Sami Chatti

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Optimization of machine learning methods for de-anonymization in social networks by Nurzhigit Smailov, Fatima Uralova, Rashida Kadyrova, Raiymbek Magazov, Akezhan Sabibolda

“…In experiments conducted on real and synthetic data, the optimized models consistently outperform baseline methods on average. Even in cases where they do not, significant improvements in precision are observed. …”
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Transfer Learning Methods for Hate Speech Detection in Bahasa Indonesia by Fairuz Astari Devianty

“…To address this issue, we study whether the transfer learning method can yield improved results. This study performs extensive experiments to show that transfer learning methods are suitable for low-resource hate speech prediction. …”
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Is It Possible to Apply Multidimensional Graphical Methods in The Teaching and Learning of Economics? by Mario Arturo Ruiz Estrada

“…This article explores the effectiveness of applying a new multidimensional graphical method to the teaching and learning of economics. …”
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Research into Robust Federated Learning Methods Driven by Heterogeneity Awareness by Junhui Song, Zhangqi Zheng, Afei Li, Zhixin Xia, Yongshan Liu

“…Federated learning (FL) has emerged as a prominent distributed machine learning paradigm that facilitates collaborative model training across multiple clients while ensuring data privacy. …”
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Application of methods of system analysis for modeling the process of distance learning by S. Ya. Zhukovich

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Application of machine learning methods for automated detection of network intrusions by M. V. Babicheva, I. A. Tretyakov

“…Such systems should be based on machine learning algorithms and models that are able to identify complex dependencies between data in the learning process.Method. …”
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Improvement of cardiovascular risk assessment using machine learning methods by A. V. Gusev, D. V. Gavrilov, R. E. Novitsky, T. Yu. Kuznetsova, S. A. Boytsov

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Machine learning methods for analyzing genomic and phenomic data in psychiatry by T. I. Nurgaliev

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