SUPPORT_VECTOR_MACHINE

作品数：782被引量：1799H指数：15
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Evaluation of underground hard rock mine pillar stability using gene expression programming and decision tree-support vector machine models
《Deep Underground Science and Engineering》2025年第1期18-34,共17页Mohammad H.Kadkhodaei Ebrahim Ghasemi Jian Zhou Melika Zahraei 
Assessing the stability of pillars in underground mines(especially in deep underground mines)is a critical concern during both the design and the operational phases of a project.This study mainly focuses on developing...
关键词：decision tree-support vector machine(DT-SVM) gene expression programming(GEP) hard rock pillar stability underground mining 
Byzantine-robust distributed support vector machine
《Science China Mathematics》2025年第3期707-728,共22页Xiaozhou Wang Weidong Liu Xiaojun Mao 
supported by National Natural Science Foundation of China (Grant No. 12101240);supported by National Natural Science Foundation of China (Grant No. 11825104);supported by National Natural Science Foundation of China (Grant Nos. 12371273 and 12001109);the Chenguang Program of Shanghai Education Development Foundation and Shanghai Municipal Education Commission (Grant No. 20CG29);the Shanghai Sailing Program (Grant No. 21YF1410500);the Shanghai Rising-Star Program (Grant No. 23QA1404600)。
The development of information technology brings diversification of data sources and large-scale data sets and calls for the exploration of distributed learning algorithms. In distributed systems, some local machines ...
关键词：Byzantine robustness CONVERGENCE distributed learning support vector machine 
Dynamic changes of spontaneous brain activity in patients after LASIK:a resting-state fMRI study
《International Journal of Ophthalmology(English edition)》2025年第3期487-495,共9页Hui Zhang Zi-Song Xu Jin-Yu Hu Zhen-Zhe Liu Lei Zhong Liang-Qi He Cheng Chen Xiao-Yu Wang Hong Wei Yan-Mei Zeng Qian Ling Xu Chen Yi-Xin Wang Yi Shao 
Supported by National Natural Science Foundation of China(No.82160195;No.82460203);Key R&D Program of Jiangxi Province(No.20223BBH80014).
AIM:To investigate changes in local brain activity after laser assisted in situ keratomileusis(LASIK)in myopia patients,and further explore whether post-LASIK(POL)patients and healthy controls(HCs)can be distinguished...
关键词：laser assisted in situ keratomileusis resting-state functional magnetic resonance imaging dynamic brain activity amplitude of low-frequency fluctuations support vector machine 
An Effective Intrusion Detection System Based on the FSA-BGRU Hybrid Model
《China Communications》2025年第2期188-198,共11页Deng Zaihui Li Zihang Guo Jianzhong Gan Guangming Kong Dejin 
supported in part by the National Natural Science Foundation of China(No.62001333);the Scientific Research Project of Education Department of Hubei Province(No.D20221702).
Intrusion detection systems play a vital role in cyberspace security.In this study,a network intrusion detection method based on the feature selection algorithm(FSA)and a deep learning model is developed using a fusio...
关键词：bidirectional GRU feature selection intrusion detection system multilayer perceptron recursive feature elimination support vector machine 
Optimization method of conditioning factors selection and combination for landslide susceptibility prediction
《Journal of Rock Mechanics and Geotechnical Engineering》2025年第2期722-746,共25页Faming Huang Keji Liu Shuihua Jiang Filippo Catani Weiping Liu Xuanmei Fan Jinsong Huang 
funded by the Natural Science Foundation of China(Grant Nos.42377164 and 41972280);the Badong National Observation and Research Station of Geohazards(Grant No.BNORSG-202305).
Landslide susceptibility prediction(LSP)is significantly affected by the uncertainty issue of landslide related conditioning factor selection.However,most of literature only performs comparative studies on a certain c...
关键词：Landslide susceptibility prediction Conditioning factors selection Support vector machine Random forest Rough set Artificial neural network 
Analysing Effectiveness of Sentiments in Social Media Data Using Machine Learning Techniques
《Journal of Computer and Communications》2025年第1期136-151,共16页Thambusamy Velmurugan Mohandas Archana Ajith Singh Nongmaithem 
Every second, a large volume of useful data is created in social media about the various kind of online purchases and in another forms of reviews. Particularly, purchased products review data is enormously growing in ...
关键词：Support Vector Machine Random Forest Algorithm Naive Bayes Algorithm Machine Learning Techniques Decision Tree Algorithm 
A Support Vector Machine(SVM)Model for Privacy Recommending Data Processing Model(PRDPM)in Internet of Vehicles
《Computers, Materials & Continua》2025年第1期389-406,共18页Ali Alqarni 
supported by the Deanship of Graduate Studies and Scientific Research at University of Bisha for funding this research through the promising program under grant number(UB-Promising-33-1445).
Open networks and heterogeneous services in the Internet of Vehicles(IoV)can lead to security and privacy challenges.One key requirement for such systems is the preservation of user privacy,ensuring a seamless experie...
关键词：Support vector machine big data IoV PRIVACY-PRESERVING 
Evaluations of Machine Learning Algorithms Using Simulation Study
《Open Journal of Statistics》2025年第1期41-52,共12页Nasrin Khatun 
1st cases of COVID-19 were reported in March 2020 in Bangladesh and rapidly increased daily. So many steps were taken by the Bangladesh government to reduce the outbreak of COVID-19, such as masks, gatherings, local m...
关键词：Linear Regression K-Nearest Neighbours Decision Tree Random Forest Support Vector Machine Hyper-Tuning 
Machine Learning Techniques in Predicting Hot Deformation Behavior of Metallic Materials
《Computer Modeling in Engineering & Sciences》2025年第1期713-732,共20页Petr Opela Josef Walek Jaromír Kopecek 
supported by the SP2024/089 Project by the Faculty of Materials Science and Technology,VˇSB-Technical University of Ostrava.
In engineering practice,it is often necessary to determine functional relationships between dependent and independent variables.These relationships can be highly nonlinear,and classical regression approaches cannot al...
关键词：Machine learning Gaussian process regression artificial neural networks support vector machine hot deformation behavior 
Non-destructive detection of chicken freshness based on multiple features image fusion and support vector machine
《International Journal of Agricultural and Biological Engineering》2024年第6期264-272,共9页Xiuguo Zou Chengrui Xin Chenyang Wang Yuhua Li Shuchen Wang Wentian Zhang Jiao Jiao Li Steven Su Maohua Xiao 
funded by the International Science and Technology Cooperation Program of Jiangsu Province(Grant No.BZ2023013);the Xuzhou Key Research and Development Project(Modern Agriculture)(Grant No.KC21135).
With the rise in global meat consumption and chicken becoming a principal source of white meat,methods for efficiently and accurately determining the freshness of chicken are of increasing importance,since traditional...
关键词：chicken freshness color space gray level co-occurrence matrix multiple features image fusion machine learning 
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