Assessment of binary prediction of fraudulent advertisements in ATS candidate tracking cloud systems by V. V. Ligi-Goryaev, G. A. Mankaeva, T. B. Goldvarg, S. S. Muchkaeva, E. N. Dzhakhnaeva

“…Traditional classification algorithms, including LSVC (Support Vector Machine), GBT (Gradient Boosting Tree), and RF (Random Forest), have been chosen for this study. …”
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Empirical Analysis of Honeybees Acoustics as Biosensors Signals for Swarm Prediction in Beehives by Kainat Iqbal, Bayan Alabdullah, Naif Al Mudawi, Asaad Algarni, Ahmad Jalal, Jeongmin Park

“…We use Naive Bayes, K-nearest Neighbors (KNN), and Support Vector Machines (SVM) as machine learning models and Convolution Neural Networks (CNN), Long Short Term Memory (LSTM), and Transformers as deep learning models for comparison purposes. …”
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Retinal Microvascular Characteristics—Novel Risk Stratification in Cardiovascular Diseases by Alexandra Cristina Rusu, Klara Brînzaniuc, Grigore Tinica, Clément Germanese, Simona Irina Damian, Sofia Mihaela David, Raluca Ozana Chistol

“…We evaluated the precision of several classification models in identifying patients with CHDs based on traditional risk factors and OCTA characteristics: a conventional logistic regression model and four machine learning algorithms: k-Nearest Neighbors (k-NN), Naive Bayes, Support Vector Machine (SVM) and supervised logistic regression. …”
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Corrosion rate prediction for long-distance submarine pipelines based on MWIWOA-SVM by Zhengshan LUO, Haipeng LYU, Jihao LUO

“…Most existing models rely on Support Vector Machine (SVM), which has limitations including low convergence accuracy, unbalanced optimization, and a tendency to get stuck in local optima. …”
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Pesticide Residue Detection in Broccoli Based on Hyperspectral Technology and Convolutional Neural Network by Dan WANG, Yuqing LUAN, Zuojun TAN, Wei WEI

“…A support vector machine (SVM) recognition model was established for pesticide residue discrimination. …”
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Real Time Intrusion Detection System Based on Web Log File Analysis by Rawand Raouf Abdalla, Alaa Khalil Jumaa, Ahmad Freidoon Fadhil

“…The model was constructed using four machine learning algorithms: gradient-boosted trees, decision tree, random forest, and support vector machine. …”
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Methodology For Extracting Poplar Planted Fields From Very High-Resolution Imagery Using Object-Based Image Analysis and Feature Selection Strategy by E. O. Yilmaz, T. Kavzoglu, I. Colkesen, H. Tonbul, A. Teke

“…Object-based image analysis (OBIA) through the application of the multi-resolution segmentation method (MRS) was employed to generate image segments, and then three prevailing machine learning algorithms, namely Support Vector Machine (SVM), Random Forest (RF) and Rotation Forest (RotFor) were implemented to produce LULC maps of the study area including 11 landscape features. …”
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Predicting the Toxicity of Drug Molecules with Selecting Effective Descriptors Using a Binary Ant Colony Optimization (BACO) Feature Selection Approach by Yuanyuan Dan, Junhao Ruan, Zhenghua Zhu, Hualong Yu

“…Only those high-frequency features are used to train a support vector machine (SVM) and construct the structure–activity relationship (SAR) prediction model. …”
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Revolutionizing agri-food technology: Development and validation of the Portable Intelligent Oil Recognition System (PIORS) by Montaser N.A. Ramadan, Mohammed A.H. Ali, Shin Yee Khoo, Layth Hamad, Mohammad Alkhedher

“…The device's innovative design integrates an advanced sensor array with seamless Bluetooth connectivity, offering real-time data synchronization with mobile applications. Several Machine learning models, including Support Vector Machines (SVM), AdaBoost, Random Forest, K-Nearest Neighbors (K-NN), Gradient-Boosting Decision Tree (GBDT), and Extreme Gradient Boosting (XGBoost) were implemented and thoroughly validated to obtain correct categorization. …”
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Landslide hazard early warning method for rock slopes using a hybrid LSTM-SARIMA data-driven model. by Yongxin Dai, Zijian Li, Jingbiao Lu

“…The excellence of the hybrid-driven model was determined by introducing five data-driven models, a Support Vector Machine (SVM), a Random Forest (RF),eXtreme Gradient Boosting (XGBoost),Recurrent Neural Network(RNN) and Light Gradient Boosting Machine(LightGBM), for comparison.Finally, the improved tangent angle of the T-t curve is employed as the landslide warning criterion, enabling accurate prediction of landslide events in an open-pit mine in East China. …”
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Holistic Pose Estimation and Dynamic Motion Analysis for Telerehabilitation of Physically Disabled Individuals by Aleena Kamal, Shaheryar Najam, Mohammed Alshehri, Yahya AlQahtani, Abdulmonem Alshahrani, Bayan Alabdullah, Jeongmin Park

“…The proposed pipeline begins with depth image preprocessing, followed by human detection using a pre-trained Histogram of Oriented Gradients (HOG)-Support Vector Machine (SVM) model. The human silhouette is segmented using the GrabCut algorithm, enabling robust region-of-interest extraction. …”
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Land use land cover change detection using multi-temporal Landsat imagery in the North of Congo Republic: a case study in Sangha region by Loubelo Madiela Bill Donatien, Bouka Biona Clobite, Missamou Lemvo Meris Midel

“…This study aims at evaluating LULC changes for the years 2013, 2018, and 2023 in the Sangha area using Landsat-8 OLI images. The Support Vector Machine (SVM) algorithm was implemented for detecting changes in the Sangha area. …”
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An analytical examination of the performance assessment of CNN-LSTM architectures for state-of-health evaluation of lithium-ion batteries by Arun Jose, Sonam Shrivastava

“…Various learning models were employed to analyze the data obtained from this hardware, with the support vector machine-based model delivering the most accurate results, showing an error rate of .48 percent. …”
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Enhancing Image Denoising Performance of Bidimensional Empirical Mode Decomposition by Improving the Edge Effect by Feng-Ping An, Da-Chao Lin, Xian-Wei Zhou, Zhihui Sun

“…This approach includes two steps, in which the first one is an extrapolation operation through the regression model constructed by the support vector machine (SVM) method with high generalization ability, based on the information of the original signal, and the second is an expansion by the closed-end mirror expansion technique with respect to the extrema nearest to and beyond the edge of the data resulting from the first operation. …”
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Optimal Band Configuration for the Roof Surface Characterization Using Hyperspectral and LiDAR Imaging by Prakash Nimbalkar, Anna Jarocinska, Bogdan Zagajewski

“…The optimal bands were investigated using supervised classifiers such as artificial neural network (ANN), support vector machine (SVM), and spectral angle mapper (SAM) by comparing accuracies. …”
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Application of Unsupervised Feature Selection in Cashmere and Wool Fiber Recognition by Yaolin Zhu, Xingze Wang, Meihua Gu, Gang Hu, Wenya Li

“…Finally, the optimal subset of features obtained by unsupervised feature selection algorithms is fed into a support vector machine for automatic identification and classification of the two fibers. …”
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Identifying the Geographical Origin of Wolfberry Using Near-Infrared Spectroscopy and Stacking-Orthogonal Linear Discriminant Analysis by Shijie Song, Xiaohong Wu, Mingyu Li, Bin Wu

“…Four classifiers—K-Nearest Neighbors (KNN), Decision Tree, Support Vector Machine (SVM), and Naive Bayes—were used to explore 12 stacked combinations on 400 samples from five regions in Gansu: Zhangye, Yumen, Wuwei, Baiyin, and Dunhuang. …”
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DETECTION OF Β THALASSEMIA CARRIERS BY RED CELL PARAMETERS OBTAINED FROM AUTOMATIC COUNTERS USING MATHEMATICAL FORMULAS by Idit Lachover Roth, Boaz Lachover, Guy Koren, Carina Levin, Luci Zalman, Ariel Koren

“…METHODS: We applied a mathematical method based on the support vector machine (SVM) algorithm in the search for a reliable formula that can differentiate between thalassemia carriers and non-carriers, including normal counts or counts suspected to belong to iron-deficient women. …”
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Gearbox Fault Diagnosis Based on Adaptive Variational Mode Decomposition–Stationary Wavelet Transform and Ensemble Refined Composite Multiscale Fluctuation Dispersion Entropy by Xiang Wang, Yang Du, Xiaoting Ji

“…Ultimately, the outcomes of the faults diagnoses are derived through the utilization of a Support Vector Machine with a Sparrow Search Algorithm (SSA-SVM), with the actual faults data collection and analysis conducted on an experimental platform for gearbox fault diagnosis. …”
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Data Mining Techniques for Iraqi Biochemical Dataset Analysis by Sarah Sameer, Suhad Faisal Behadili

“…Then the preprocessing step performed, to make the dataset analyzable by supervised techniques such as Linear Discriminant Analysis (LDA), Classification And Regression Tree (CART), Logistic Regression (LR), K-Nearest Neighbor (K-NN), Naïve Bays (NB), and Support Vector Machine (SVM) techniques. CART gives clear results with high accuracy between the six supervised algorithms. …”
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