Spatiotemporal dynamics and key drivers of carbon emissions in regional construction sectors: Insights from a Random Forest Model by Zhonghan Yu, Qudsia Kanwal, Menghan Wang, Anissa Nurdiawati, Sami G. Al-Ghamdi

“…This research utilizes the Random Forest Model, a sophisticated machine learning method, to examine the determinants of carbon emissions in China's construction sector at the regional scale. …”
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A Multi-Stage Feature Selection and Explainable Machine Learning Framework for Forecasting Transportation CO₂ Emissions by Mohammad Ali Sahraei, Keren Li, Qingyao Qiao

“…The transportation sector is a major consumer of primary energy and is a significant contributor to greenhouse gas emissions. …”
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Classification Based on the Support Vector Machine for Determining Operational Targets for Controlling Electricity Usage With Conventional Meters: A Case Study of Industrial and Bu... by Galih Arisona, Alief Pascal Taruna, Dwi Irwanto, Arif Bijak Bestari, Wildan Juniawan

“…This research aims to improve the detection of electricity theft through a machine learning-based model utilizing the Support Vector Machine (SVM) classification technique. …”
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Integrating routine blood biomarkers and artificial intelligence for supporting diagnosis of silicosis in engineered stone workers by Daniel Sanchez‐Morillo, Antonio León‐Jiménez, María Guerrero‐Chanivet, Gema Jiménez‐Gómez, Antonio Hidalgo‐Molina, Antonio Campos‐Caro

“…The percentage of lymphocytes, the angiotensin‐converting enzyme, and lactate dehydrogenase indexes were revealed, among others, as blood biomarkers with significant cumulative importance for the machine learning models. Our study reveals that these biomarkers could detect a chronic inflammatory status and potentially serve as a supportive tool for the diagnosis, monitoring, and early detection of the progression of silicosis.…”
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Comparative Analysis of a Quantum SVM With an Optimized Kernel Versus Classical SVMs by Matheus Cammarosano Hidalgo

“…Support Vector Machine (SVM) is a widely used algorithm for classification, valued for its flexibility with kernels that effectively handle non-linear problems and high-dimensional data. …”
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An explainable machine learning framework for railway predictive maintenance using data streams from the metro operator of Portugal by Silvia García-Méndez, Francisco de Arriba-Pérez, Fátima Leal, Bruno Veloso, Benedita Malheiro, Juan Carlos Burguillo-Rial

“…Abstract The public transportation sector generates large volumes of sensor data that, if analyzed adequately, can help anticipate failures and initiate maintenance actions, thereby enhancing quality and productivity. …”
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Advancements and gaps in natural language processing and machine learning applications in healthcare: a comprehensive review of electronic medical records and medical imaging by Priyanka Khalate, Shilpa Gite, Shilpa Gite, Biswajeet Pradhan, Chang-Wook Lee

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Crop yield prediction in agriculture: A comprehensive review of machine learning and deep learning approaches, with insights for future research and sustainability by Md. Abu Jabed, Masrah Azrifah Azmi Murad

“…The research paper also examines the algorithms frequently utilized in the machine learning domain, including Random Forest (RF), Artificial Neural Networks (ANN), and Support Vector Machine (SVM). …”
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Early Prediction Detection of Retail and Corporate Credit Risks Using Machine Learning Algorithms by Mohamed A. Hamada, Karim Farag, Adejor E. Abiche

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Servitization on the primary sector – coffee plantations case by Rebecca Impelizieri Moura da Silveira, Noel Torres Júnior, Rafael Teixeira, Ana Correia Simões

“…However, the characteristics of rural properties seem to affect the number of services associated with machine suppliers. The results support managers in this sector to identify service offerings and widen the discussion about servitization by covering a barely explored sector. …”
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Komparasi Algoritma Support Vector Machines dengan Algoritma Artificial Neural Network untuk Memprediksi Nilai Persetujuan Kredit Modal Kerja yang Diberikan Bank Umum by Abu Sopian, Agus Wiyatno, Albert Riyandi

“…Working capital credit approval provided by commercial bank need to predict because it has increased of credit provision provided by commercial bank that can be used as measurement of economic growth and country stability or as measurement of economic growth indicator from monetary sector by Bank of Indonesia. In this research will conducted working capital credit value approval prediction will be provided by commercial bank using support vector machine algorithm that is compared with artificial neutral network algorithm. …”
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Automated System for OEE Management in the Industrial Sector by Diego Gomez, Sofia Pantoja, Enoc Acosta, David Arrieta, Sebastián Gutiérrez

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Advancing tourism demand forecasting in Sri Lanka: evaluating the performance of machine learning models and the impact of social media data integration by Isuru Udayangani Hewapathirana

“…Purpose – This study explores the pioneering approach of utilising machine learning (ML) models and integrating social media data for predicting tourist arrivals in Sri Lanka. …”
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Enhancing revenue generation in Bangladesh’s FinTech sector: a comprehensive analysis of real-time predictive customer behavior modeling in AWS using a hybrid OptiBoost-EnsembleX m... by Avijit Chowdhury

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A Comparative Study of Machine Learning and Deep Learning Models for Automatic Parkinson’s Disease Detection from Electroencephalogram Signals by Sankhadip Bera, Zong Woo Geem, Young-Im Cho, Pawan Kumar Singh

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Clustering and Vectorizing Acoustic Emission Events of Large Infrastructures’ Normal Operation by Theocharis Tsenis, Vassilios Kappatos

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Comparison of Rating-based and Inset Lexicon-based Labeling in Sentiment Analysis using SVM (Case Study: GoBiz Application Reviews on Google Play Store) by Hiliah Firda, Pacu Putra, Nabila Rizky Oktadini, Putri Eka Sevtiyuni, Allsela Meiriza

“…It compares two labeling methods—Rating-Based and Inset Lexicon—and evaluates them using the Support Vector Machine (SVM) algorithm. The analysis process includes data selection, text preprocessing, data transformation using TF-IDF, SVM implementation with 10-fold cross-validation, and result visualization through word clouds. …”
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Dynamic Workload Management System in the Public Sector: A Comparative Analysis by Konstantinos C. Giotopoulos, Dimitrios Michalopoulos, Gerasimos Vonitsanos, Dimitris Papadopoulos, Ioanna Giannoukou, Spyros Sioutas

“…Using a dataset encompassing public/private sector experience, educational history, and age, we evaluate the effectiveness of seven machine learning algorithms: Linear Regression, Artificial Neural Networks (ANNs), Adaptive Neuro-Fuzzy Inference System (ANFIS), Support Vector Machine (SVM), Gradient Boosting Machine (GBM), Bagged Decision Trees, and XGBoost in predicting employee capability and optimizing task allocation. …”
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Harnessing automation techniques for supporting sustainability in agriculture by Mustafa A. J. Al-sammarraie, Ali Irfan Ilbas

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Obstetrical ultrasound training of and practise by general practitioners in the private sector, Free State by S. Foulkes, G. Joubert, B.L. Faber, L.A. Hiemstra

“…Background: The aim of the study was to determine the level of obstetrical ultrasound training and practice of general practitioners in the Free State private sector. Methods: In this descriptive study, questionnaires were mailed to all general practitioners in the Free State private sector. …”
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