Hybrid RGSA and Support Vector Machine Framework for Three-Dimensional Magnetic Resonance Brain Tumor Classification by R. Rajesh Sharma, P. Marikkannu

“…The optimal features are selected using the proposed refined gravitational search algorithm (RGSA). Support vector machines, over backpropagation network, and k-nearest neighbor are used to evaluate the goodness of classifier approach. …”
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The Application of Support Vector Machine (SVM) in Industrial Carbon Accounting Prediction and Green Electricity Control Strategies by Xu Shasha, Wu Haipeng, Luo Junting, Chen Jian, Jia Huihan

“…This paper, based on the Support Vector Machine (SVM) model, explores its application in industrial carbon accounting, focusing on the interaction between carbon emissions prediction and optimization of control strategies. …”
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Virtual Screening of Conjugated Polymers for Organic Photovoltaic Devices Using Support Vector Machines and Ensemble Learning by Fang-Chung Chen

“…Herein, we report virtual screening of potential semiconductor polymers for high-performance organic photovoltaic (OPV) devices using various machine learning algorithms. We particularly focus on support vector machine (SVM) and ensemble learning approaches. …”
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Support vector machine based fast Monte Carlo reliability evaluation method for composite power system by Yuxiao LEI, Gengfeng LI, Yuxiong HUANG, Zhaohong BIE

“…A fast Monte Carlo reliability evaluation method for composite power system based on support vector machine (SVM) was proposesd.Firstly,sample data for training the SVM model was obtained by enumerating component failures and calculating the corresponding minimum load shedding.Then,the SVM algorithm was used to mine the nonlinear mapping relationship between component failures and minimum load shedding,and the minimum load shedding estimation model was trained.Finally,the model was combined with the Monte Carlo simulation.By randomly sampling component states,for each state,the estimation model obtained by the training directly gave the minimum load shedding,thereby achieving a rapid assessment of the reliability of the composite power system.The proposed method is applied to the IEEE RTS 79 system,which verifies its effectiveness.…”
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Fault Diagnosis of Vehicle Gearbox based on Support Vector Machine Optimized by Improved Beetle Antennae Search by Wenshan Qiao, Jin Hua, Meihong Chen

“…Aiming at the fact that the performance of support vector machine （SVM） in vehicle gearbox fault diagnosis is greatly affected by parameters，a new method of vehicle gearbox fault diagnosis based on improved SVM is proposed based on the research of beetle antennae search （BAS）. …”
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A FAULT DIAGNOSIS METHOD BASED ON IMPROVED ARTIFICAL BEE COLONY OPTIMIZE SUPPORT VECTOR MACHINE by WU YinHua, XU QiongYan

“…Aiming at the fact that the fault diagnosis performance of support vector machine（ SVM） highly depends on the parameters selection,a fault diagnosis method based on improved artificial bee colony（ IABC） optimize SVM was proposed. …”
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Diagnosis of Encephalopathy Based on Energies of EEG Subbands Using Discrete Wavelet Transform and Support Vector Machine by Jisu Elsa Jacob, Gopakumar Kuttappan Nair, Thomas Iype, Ajith Cherian

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Deep learning and support vector machine-recursive feature elimination-based network intrusion detection model by YE Qing, ZHANG Yannian, WU Hao

“…The features were sorted by the support vector machine-recursive feature elimination algorithm and the important features were selected. …”
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Dynamics-Guided Support Vector Machines for Response Analysis of Steel Frame Under Sine Wave Excitation by Yao Wang, Huaiman Li

“…To address this issue, a novel dynamics-guided support vector machine (DG-SVM) method is proposed, which embeds an optimization process to reduce dependence on the time step size. …”
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APPLICATION OF THE SUPPORT VECTOR MACHINE, LIGHT GRADIENT BOOSTING MACHINE, ADAPTIVE BOOSTING, AND HYBRID ADABOOST-SVM MODEL ON CUSTOMERS CHURN DATA by Felice Elena, Robyn Irawan, Benny Yong

“…This paper will use the Support Vector Machine (SVM), Light Gradient Boosting Machine (LightGBM), and hybrid Adaptive Boosting-SVM (AdaBoost-SVM) model. …”
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PERBANDINGAN KERNEL SUPPORT VECTOR MACHINE (SVM) DALAM PENERAPAN ANALISIS SENTIMEN VAKSINISASI COVID-19 by Thalita Meisya Permata Aulia, Nur Arifin, Rini Mayasari

“…For this reason, a sentiment analysis of the COVID-19 vaccine will be carried out by taking data from Twitter, then classified using the Support Vector Machine algorithm. The research data is nonlinear data so it requires a kernel space for the text mining process, while there has been no specific research regarding which kernel is good for sentiment analysis, so a test will be carried out to find the best kernel among linear, sigmoid, polynomial, and RBF kernels. …”
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Rapid and Low-Cost Detection of Thyroid Dysfunction Using Raman Spectroscopy and an Improved Support Vector Machine by Xiangxiang Zheng, Guodong Lv, Guoli Du, Zhengang Zhai, Jiaqing Mo, Xiaoyi Lv

“…This study presents a rapid and low-cost method to detect thyroid dysfunction using serum Raman spectroscopy combined with support vector machine (SVM). The serum samples taken from 34 thyroid dysfunction patients and 40 healthy volunteers were measured in this study. …”
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Support Vector Machine – Recursive Feature Elimination for Feature Selection on Multi-omics Lung Cancer Data by Nuraina Syaza Azman, Azurah A Samah, Ji Tong Lin, Hairudin Abdul Majid, Zuraini Ali Shah, Nies Hui Wen, Chan Weng Howe

“…The study focuses on mitigating the curse of dimensionality by implementing Support Vector Machine – Recursive Feature Elimination (SVM-RFE) as the selected feature selection method in the lung cancer (LUSC) multi-omics dataset integrated from three single omics dataset comprising genomics, transcriptomics and epigenomics, and assess the quality of the selected feature subsets using SDAE and VAE deep learning classifiers. …”
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Assessment of the Aging State for Transformer Oil-Barrier Insulation by Raman Spectroscopy and Optimized Support Vector Machine by Deliang Liu, Biao Lu, Wenping Wu, Wei Zhou, Wansu Liu, Yiye Sun, Shilong Wu, Guolong Shi, Leiming Yuan

“…The raw Raman spectra were processed using asymmetric reweighted penalty least squares to correct baseline shifts, Savitzky–Golay (S-G) smoothing to eliminate fluctuation noise, and principal component analysis (PCA) to reduce data dimensionality by extracting principal components. A support vector machine (SVM) classifier was developed to discriminate between the Raman spectra and category labels. …”
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Machine Learning and Deep Learning Models for Dengue Diagnosis Prediction: A Systematic Review by Daniel Cristobal Andrade Girón, William Joel Marín Rodriguez, Flor de María Lioo-Jordan, Jose Luis Ausejo Sánchez

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Applying Radom Forest and Support Vector Machine for Land-use Classification in Phu Giao District Vietnam by Trong Dieu Hien Le, Linh Truong Vinh

“…Support vector machines (SVMs) and random forests (RFs) are more effective ML algorithms and more accurate classifications than other methods. …”
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A Novel Homogenous Hybridization Scheme for Performance Improvement of Support Vector Machines Regression in Reservoir Characterization by Kabiru O. Akande, Taoreed O. Owolabi, Sunday O. Olatunji, AbdulAzeez Abdulraheem

“…In this work, a novel homogenous hybridization scheme is proposed for the improvement of the generalization and predictive ability of support vector machines regression (SVR). The proposed and developed hybrid SVR (HSVR) works by considering the initial SVR prediction as a feature extraction process and then employs the SVR output, which is the extracted feature, as its sole descriptor. …”
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Sentiment Analysis for the 2024 DKI Jakarta Gubernatorial Election Using a Support Vector Machine Approach by Mariani Mariani, Dwi Shinta Angreni, Sri Khaerawati Nur, Rinianty Rinianty, Deni Luvi Jayanto

“…This study analyzes public sentiment regarding candidates in the 2024 DKI Jakarta Gubernatorial Election utilizing a Support Vector Machine (SVM) approach. Recognizing the pivotal role of social media, particularly Twitter, in shaping public opinion, the research addresses the challenges of processing large volumes of unstructured data. …”
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Near-Infrared Spectroscopy Combined With Support Vector Machine Model to Realize Quality Control of Ginkgolide Production by Lei Liu, Jun Wang, Haiyi Bian, Ahmed N. Abdalla

“…This study addresses this concern by leveraging chemometric models, specifically partial least squares (PLS), support vector machine (SVM), and random forest, in conjunction with near-infrared spectroscopy (NIRS) data. …”
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Machine Learning and Metaheuristic Algorithms for Voice-Based Authentication: A Mobile Banking Case Study by Leili Nosrati, Amir Massoud Bidgoli, Hamid Haj Seyyed Javadi

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