Safe transductive support vector machine by Haiyan Chen, Ying Yu, Yizhen Jia, Linghui Zhang

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Optimizing Data Classification in Support Vector Machines Using Metaheuristic Algorithms by Qonita Ilmi Awalin, Ika Hesti Agustin, Alfian Futuhul Hadi, Dafik Dafik, R. Sunder

“…To categorize patient diagnosis data related to Chronic Kidney Disease (CKD), this study compares the classification performance of Support Vector Machines (SVM) enhanced by Particle Swarm Optimization (PSO) and Genetic Algorithm (GA). …”
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Research on Speech and Emotional Recognition Algorithm Based on Support Vector Machine by LIU Ming-zhu, LI Xiao-qin, CHEN Hong-heng

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Parameter Optimisation of Support Vector Machine using Genetic Algorithm for Cyberbullying Detection by Mohd Qorib Alqowiy, Ema Utami

“…To address this issue, many researchers have proposed solutions for detecting cyberbullying. Among these, the Support Vector Machine (SVM) method is commonly used because it delivers more accurate results compared to other algorithms. …”
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Combining the Multi-Genetic Algorithm and Support Vector Machine for Fault Diagnosis of Bearings by Jianbin Xiong, Qinghua Zhang, Qiong Liang, Hongbin Zhu, Haiying Li

“…Overstudy or understudy phenomena can sometimes occur due to the strong dependence of support vector machine (SVM) algorithms on particular parameters and the lack of systems theory relating to parameter selection. …”
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Botnet Detection Using Support Vector Machines with Artificial Fish Swarm Algorithm by Kuan-Cheng Lin, Sih-Yang Chen, Jason C. Hung

“…The proposed method is a classified model in which an artificial fish swarm algorithm and a support vector machine are combined. …”
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An optimized support vector machine for lung cancer classification system by Mayowa O. Oyediran, Olufemi S. Ojo, Ibrahim A. Raji, Abidemi Emmanuel Adeniyi, Oluwasegun Julius Aroba, Oluwasegun Julius Aroba

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The Application Based on Support Vector Machine Optimized by Particle Swarm Optimization and Genetic Algorithm by MAN Chun-tao, LIU Bo, CAO Yong-cheng

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Financial Fraud Detection Approach Based on Firefly Optimization Algorithm and Support Vector Machine by Ajeet Singh, Anurag Jain, Seblewongel Esseynew Biable

“…In this paper, a new methodology has been proposed for detecting credit card fraud (financial fraud) that is a hybridization of the firefly bio-inspired optimization algorithm and a support vector machine (called FFSVM), which comprises two sequential levels. …”
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Classification of Service Sentiments on the by.U Application using the Support Vector Machine Algorithm by Zulkarnain Zulkarnain, Rice Novita, Angraini Angraini, Zarnelly Zarnelly

“…This study aims to classify user sentiment toward the by.U application service using the Support Vector Machine (SVM) algorithm. The background of this research is based on the importance of understanding user opinions on the quality of digital services as a basis for evaluation and service improvement. …”
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Research on Sleep Staging Based on Support Vector Machine and Extreme Gradient Boosting Algorithm by Wang Y, Ye S, Xu Z, Chu Y, Zhang J, Yu W

“…Yiwen Wang,1 Shuming Ye,2 Zhi Xu,3 Yonghua Chu,1 Jiarong Zhang,4 Wenke Yu5 1Clinical Medical Engineering Department, The Second Affiliated Hospital, Zhejiang University School of Medicine, HangZhou, ZheJiang, People’s Republic of China; 2Department of Biomedical Engineering, Zhejiang University, HangZhou, ZheJiang, People’s Republic of China; 3China Astronaut Research and Training Center, BeiJing, People’s Republic of China; 4Baidu Inc, BeiJing, People’s Republic of China; 5Radiology Department, ZheJiang Province Qing Chun Hospital, HangZhou, ZheJiang, People’s Republic of ChinaCorrespondence: Yiwen Wang; Shuming Ye, Email karenkaren2010@zju.edu.cn; ysmln@vip.sina.comPurpose: To develop a sleep-staging algorithm based on support vector machine (SVM) and extreme gradient boosting model (XB Boost) and evaluate its performance.Methods: In this study, data features were extracted based on physiological significance, feature dimension reduction was performed through appropriate methods, and XG Boost classifier and SVM were used for classification. …”
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Modelling Soil Water Retention Using Support Vector Machines with Genetic Algorithm Optimisation by Krzysztof Lamorski, Cezary Sławiński, Felix Moreno, Gyöngyi Barna, Wojciech Skierucha, José L. Arrue

“…The developed models allowed for estimation of the soil water content for the specified soil water potentials: –0.98, –3.10, –9.81, –31.02, –491.66, and –1554.78 kPa, based on the following soil characteristics: soil granulometric composition, total porosity, and bulk density. Support Vector Machines (SVM) methodology was used for model development. …”
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Genetic Artificial Hummingbird Algorithm-Support Vector Machine for Timely Power Theft Detection by Emmanuel Gbafore, Davies Rene Segera, Cosmas Raymond Mutugi Kiruki

“…This study presents a novel hybrid genetic artificial hummingbird algorithm-support vector machine classifier to detect power theft. …”
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Analysis of Public Perception on Domestic Violence Cases using Support Vector Machine Algorithm by Mirdatul Husnah, Rahmat Hidayat

“…The analysis was conducted using the Support Vector Machine algorithm, a classification algorithm that can classify values into certain classes and has a good level of accuracy. …”
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PERFORMANCE PREDICTION OF ROADHEADERS USING SUPPORT VECTOR MACHINE (SVM), FIREFLY ALGORITHM (FA) AND BAT ALGORITHM (BA) by Arash Ebrahimabadi, Alireza Afradi

“…Additionally, this study employed Firefly Algorithm (FA), Bat Algorithm (BA) and Support Vector Machine (SVM), which were assessed using coefficient of determination (R²), root mean square error (RMSE), mean squared error (MSE) and mean absolute error (MAE).The obtained results for Firefly Algorithm (FA) are found to be as R2 = 0.9104, RMSE = 0.0658, MSE= 0.0043 and MAE= 0.0039, for Bat Algorithm (BA) are found to be as R2 = 0.9421, RMSE = 0.0528, MSE= 0.0027 and MAE= 0.0024, and for Support Vector Machine (SVM) are found to be as R2 = 0.8795, RMSE = 0.0762, MSE= 0.0058 and MAE= 0.0052, respectively. …”
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DEVELOPMENT OF HEALTH INSURANCE CLAIM PREDICTION METHOD BASED ON SUPPORT VECTOR MACHINE AND BAT ALGORITHM by Syaiful Anam, Abdi Negara Guci, Fery Widhiatmoko, Mila Kurniawaty, Komang Agus Arta Wijaya

“…Support Vector Machine (SVM) is one of the superior ML approaches. …”
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Localization algorithm for large-scale wireless sensor networks based on FCMTSR-support vector machine by Fang Zhu, Junfang Wei

“…For a large-scale wireless sensor network, localization algorithm based on support vector machine faces to the problem of the large-scale learning samples. …”
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Stability Evaluation of Rock Slope in Hydraulic Engineering Based on Improved Support Vector Machine Algorithm by Fei Li, Hongyun Zhang

“…In this paper, a cuckoo search algorithm-improved support vector machine (CS-SVM) method is applied to slope stability analysis and parameter inversion. …”
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Research of Financial Early-Warning Model on Evolutionary Support Vector Machines Based on Genetic Algorithms by Zuoquan Zhang, Fan Lang, Qin Zhao

“…But the parameters of the kernel function which influence the result and performance of support vector machines have not been decided. Based on genetic algorithms, this paper proposes a new scientific method to automatically select the parameters of SVMs for financial early-warning model. …”
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Temperature Sensor Fault Detection in Chiller Based on One-class Support Vector Machine Algorithm by Mao Qianjun, Liang Zhiyuan, Liu Donghua, Hu Yunpeng, Li Guannan, Fang Xi

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