Computerized Interactive Gaming via Supporting Vector Machines by Y. Jiang, J. Jiang, I. J. Palmer

“…This paper describes a supporting vector machine-based artificial intelligence algorithm as one of the possible solutions to the problem of random data processing and the provision of interactive indication for further actions. …”
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Subject based feature selection for hybrid brain computer interface using genetic algorithm and support vector machine by Nida Mateen, Mehreen Naeem, Muhammad Jawad Khan, Talha Yousaf, Ahsan Ali, Wael A. Altabey, Mohammad Noori, Sallam A Kouritem

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Prediction Analysis of College Students’ Physical Activity Behavior by Improving Gray Wolf Algorithm and Support Vector Machine by Minjian Wang

“…In order to overcome the problem of low accuracy of traditional algorithms in prediction, this paper uses the improved gray wolf algorithm (IGWO) and support vector machine (SVM) for predictive analysis of college students' physical exercise behavior. …”
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Quality Evaluation Method for Base Baijiu Based on Support Vector Machine Optimized by Genetic and Bootstrap Aggregating Algorithm by PANG Tingting, ZHANG Guiyu, LIU Kecai, LI Xiaoping, TUO Xianguo, PENG Yingjie, ZENG Xianglin

Subjects: “…base baijiu; support vector machine; bootstrap aggregating; genetic algorithm; classification prediction…”
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Design of Anomaly Based Intrusion Detection System Using Support Vector Machine and Grasshopper Optimization Algorithm in IoT by Sepehr Sharifi, Soulmaz Gheisari

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User Analysis of Info BMKG Application in The Perspective of Human Computer Interaction Using Support Vector Machine Algorithm by Ilham Fannani, Enggar Novianto, Alfin Syarifuddin Syahab

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A New Hybrid Algorithm for Bankruptcy Prediction Using Switching Particle Swarm Optimization and Support Vector Machines by Yang Lu, Nianyin Zeng, Xiaohui Liu, Shujuan Yi

“…In this paper, a new hybrid algorithm combining switching particle swarm optimization (SPSO) and support vector machine (SVM) is proposed to solve the bankruptcy prediction problem. …”
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Fault Diagnosis System of Induction Motors Based on Multiscale Entropy and Support Vector Machine with Mutual Information Algorithm by Shuang Pan, Tian Han, Andy C. C. Tan, Tian Ran Lin

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Intelligent Fault Diagnosis for Rotating Mechanical Systems: An Improved Multiscale Fuzzy Entropy and Support Vector Machine Algorithm by Yuxin Pan, Yinsheng Chen, Xihong Fei, Kang Wang, Tian Fang, Jing Wang

“…Intelligent fault diagnosis technology plays a significant role in improving the reliability and safety of industrial equipment. A new algorithm based on improved multiscale fuzzy entropy and support vector machine (IMFE-SVM) is proposed for the automatic diagnosis of various fault types in elevator rotating mechanical systems. …”
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A Semisupervised Feature Selection with Support Vector Machine by Kun Dai, Hong-Yi Yu, Qing Li

“…In this paper, a novel semisupervised feature selection algorithm based on support vector machine (SVM) is proposed, termed SENFS. …”
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Classification of FAMACHA© Scores with Support Vector Machine Algorithm from Body Condition Score and Hematological Parameters in Pelibuey Sheep by Oswaldo Margarito Torres-Chable, Cem Tırınk, Rosa Inés Parra-Cortés, Miguel Ángel Gastelum Delgado, Ignacio Vázquez Martínez, Armando Gomez-Vazquez, Aldenamar Cruz-Hernandez, Enrique Camacho-Pérez, Dany Alejandro Dzib-Cauich, Uğur Şen, Hacer Tüfekci, Lütfi Bayyurt, Hilal Tozlu Çelik, Ömer Faruk Yılmaz, Alfonso J. Chay-Canul

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SVF: Support Vector Federation by Mirko Polato, Roberto Esposito, Lorenzo Sciandra

“…Support Vector Machines (SVMs), in particular, have seen limited exploration within the federated context, with existing techniques often constrained by the necessity to share the weight vector of the linear classifier. …”
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Support Vector Machine Algorithm for Mapping Land Cover Dynamics in Senegal, West Africa, Using Earth Observation Data by Polina Lemenkova

“…Two image classification methods were compared, and their performance was evaluated in the GRASS GIS software (version 8.4.0, creator: GRASS Development Team, original location: Champaign, Illinois, USA, currently multinational project) by means of unsupervised classification using the k-means clustering algorithm and supervised classification using the Support Vector Machine (SVM) algorithm. …”
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Temperature drift modeling and compensation of micro-electro-mechanical system gyroscope based on improved support vector machine algorithms by Xinwang Wang, Huiliang Cao

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Prediction of Crop Yield by Support Vector Machine Coupled with Deep Learning Algorithm Procedures in Lower Kulfo Watershed of Ethiopia by Abebe Temesgen Ayalew, Tarun Kumar Lohani

“…The support vector machine (SVM) was applied as a machine learning procedure, whereas long short-term memory (LSTM) and the recurrent neural network (RNN) were considered as deep learning procedures. …”
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Online Traffic Crash Risk Inference Method Using Detection Transformer and Support Vector Machine Optimized by Biomimetic Algorithm by Bihui Zhang, Zhuqi Li, Bingjie Li, Jingbo Zhan, Songtao Deng, Yi Fang

“…The TAR-2 dataset is inputted into a Support Vector Machine (SVM) optimized using a hybrid algorithm and used to infer the risk of urban traffic crashes. …”
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Classification of Anxiety Levels of IGD Patients at RSU Royal Prima Medan Using Support Vector Machine (SVM) Algorithm by Kharisma Gunanta Ginting, Nugroho Prasetyo, Al Vino Gunawan, Magdalena Sihombing, Adli Abdillah Nababan

“…This study aims to develop a patient anxiety level classification model in the ED using the Support Vector Machine (SVM) algorithm with the application of the Synthetic Minority Oversampling Technique (SMOTE) to address the class imbalance issue. …”
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Prediction and management of physical injuries caused by gym equipment and facilities using a Support Vector Machine (SVM) algorithm by Javad Shahlaei Bagheri

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Comparison of Support Vector Machine and Decision Tree Algorithm Performance with Undersampling Approach in Predicting Heart Disease Based on Lifestyle by Gusti Ayu Putu Febriyanti, Anna Baita

“…This study evaluates the performance of two machine learning algorithms, namely Support Vector Machine (SVM) and Decision Tree (DT), in predicting heart disease risk by applying undersampling techniques to handle data imbalance. …”
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Evaluating ground vibration attenuation through leca‐filled trenches: A support vector machine approach by Mohsen Naghizadeh Rokni, Omid Tavasoli, Reza Esmaeilabadi, Amirpouya Saraf

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