Zaloguj się

Gotowe bibliografie tematyczne / SVM / Artykuły w czasopismach

Artykuły w czasopismach na temat „SVM”

Kliknij ten link, aby zobaczyć inne rodzaje publikacji na ten temat: SVM.

Autor: Grafiati

Data publikacji: 4 czerwca 2021

Data aktualizacji: 22 czerwca 2024

Utwórz poprawne odniesienie w stylach APA, MLA, Chicago, Harvard i wielu innych

Wybierz rodzaj źródła:

Sprawdź 50 najlepszych artykułów w czasopismach naukowych na temat „SVM”.

Przycisk „Dodaj do bibliografii” jest dostępny obok każdej pracy w bibliografii. Użyj go – a my automatycznie utworzymy odniesienie bibliograficzne do wybranej pracy w stylu cytowania, którego potrzebujesz: APA, MLA, Harvard, Chicago, Vancouver itp.

Możesz również pobrać pełny tekst publikacji naukowej w formacie „.pdf” i przeczytać adnotację do pracy online, jeśli odpowiednie parametry są dostępne w metadanych.

Przeglądaj artykuły w czasopismach z różnych dziedzin i twórz odpowiednie bibliografie.

1

Wang, Bo, Yu Kai Yao, Xiao Ping Wang i Xiao Yun Chen. "PB-SVM Ensemble: A SVM Ensemble Algorithm Based on SVM". Applied Mechanics and Materials 701-702 (grudzień 2014): 58–62. http://dx.doi.org/10.4028/www.scientific.net/amm.701-702.58.

Pełny tekst źródła

Streszczenie:

As one of the most popular and effective classification algorithms, Support Vector Machine (SVM) has attracted much attention in recent years. Classifiers ensemble is a research direction in machine learning and statistics, it often gives a higher classification accuracy than the single classifier. This paper proposes a new ensemble algorithm based on SVM. The proposed classification algorithm PB-SVM Ensemble consists of some SVM classifiers produced by PCAenSVM and fifty classifiers trained using Bagging, the results are combined to make the final decision on testing set using majority voting. The performance of PB-SVM Ensemble are evaluated on six datasets which are from UCI repository, Statlog or the famous research. The results of the experiment are compared with LibSVM, PCAenSVM and Bagging. PB-SVM Ensemble outperform other three algorithms in classification accuracy, and at the same time keep a higher confidence of accuracy than Bagging.

Style APA, Harvard, Vancouver, ISO itp.

2

ZHU, Yongsheng. "A new type SVM??projected SVM". Science in China Series G 47, nr 7 (2004): 21. http://dx.doi.org/10.1360/03yb0244.

Pełny tekst źródła

Style APA, Harvard, Vancouver, ISO itp.

3

Huang, Wencheng, Hongyi Liu, Yue Zhang, Rongwei Mi, Chuangui Tong, Wei Xiao i Bin Shuai. "Railway dangerous goods transportation system risk identification: Comparisons among SVM, PSO-SVM, GA-SVM and GS-SVM". Applied Soft Computing 109 (wrzesień 2021): 107541. http://dx.doi.org/10.1016/j.asoc.2021.107541.

Pełny tekst źródła

Style APA, Harvard, Vancouver, ISO itp.

4

Yanling, Xu, Wu Baolin i Baolin Liushan. "A Network-Adapative SVC Streaming Strategy with SVM-Based Bandwidth Prediction". International Journal of Future Computer and Communication 3, nr 3 (2014): 205–9. http://dx.doi.org/10.7763/ijfcc.2014.v3.297.

Pełny tekst źródła

Style APA, Harvard, Vancouver, ISO itp.

5

SHIMADA, KAZUTAKA, KOJI HAYASHI i TSUTOMU ENDO. "Product Specification Extraction Using SVM and Transductive SVM". Journal of Natural Language Processing 12, nr 3 (2005): 43–66. http://dx.doi.org/10.5715/jnlp.12.3_43.

Pełny tekst źródła

Style APA, Harvard, Vancouver, ISO itp.

6

Huang, Min-Wei, Chih-Wen Chen, Wei-Chao Lin, Shih-Wen Ke i Chih-Fong Tsai. "SVM and SVM Ensembles in Breast Cancer Prediction". PLOS ONE 12, nr 1 (6.01.2017): e0161501. http://dx.doi.org/10.1371/journal.pone.0161501.

Pełny tekst źródła

Style APA, Harvard, Vancouver, ISO itp.

7

Lapin, Maksim, Matthias Hein i Bernt Schiele. "Learning using privileged information: SVM+ and weighted SVM". Neural Networks 53 (maj 2014): 95–108. http://dx.doi.org/10.1016/j.neunet.2014.02.002.

Pełny tekst źródła

Style APA, Harvard, Vancouver, ISO itp.

8

Safiya, K. M. "Genetic Algorithm with SRM SVM Classifier for Face Verification". International Journal of Computer Science and Information Technology 4, nr 4 (31.08.2012): 151–63. http://dx.doi.org/10.5121/ijcsit.2012.4414.

Pełny tekst źródła

Style APA, Harvard, Vancouver, ISO itp.

9

Deepthi, Medechal, Mosali Harini, Pandiri Sai Geethika, Vusirikala Kalyan i K. Kishor. "Data Classification of Dark Web using SVM and S3VM". International Journal for Research in Applied Science and Engineering Technology 11, nr 9 (30.09.2023): 510–17. http://dx.doi.org/10.22214/ijraset.2023.55643.

Pełny tekst źródła

Streszczenie:

Abstract: There are many issues regarding the dark web structural Type. It also increases the number of cybercrimes like illegal trade, forums, Terrorist activity. By understanding online criminal’s actions are challenging because the data is available in a very great extent amount. In a recent day the Online crimes are increasing all over the world. The data related to different types of frauds and scams, such as phishing schemes, identity theft etc. The data and discussion related to the act of hacking (hacktivist) activities, this often involve political or social causes. In some parts of dark web might be used for anonymous communication and the losing of sensitive information to explore wrong doing by governments or corporations. But in some countries the dark web might be used as a means to access information and content that is hardly restricted. The primary focus of this research is to develop a hybrid classification model that combines the strengths of deep learning and natural language processing algorithms. The model leverages a curated dataset of Dark Web content, meticulously labeled by content category, ranging from illegal commerce to cyber threats. By extracting relevant features from the textual and visual components of the data, the model demonstrates superior accuracy in distinguishing between different content categories

Style APA, Harvard, Vancouver, ISO itp.

10

Ardjani, Fatima, i Kaddour Sadouni. "Optimization of SVM Multiclass by Particle Swarm (PSO-SVM)". International Journal of Modern Education and Computer Science 2, nr 2 (16.12.2010): 32–38. http://dx.doi.org/10.5815/ijmecs.2010.02.05.

Pełny tekst źródła

Style APA, Harvard, Vancouver, ISO itp.

11

Aronow, Herbert D. "SVM Communications: Highlights from the 32nd SVM Scientific Sessions". Vascular Medicine 26, nr 6 (8.11.2021): 680–82. http://dx.doi.org/10.1177/1358863x211054878.

Pełny tekst źródła

Style APA, Harvard, Vancouver, ISO itp.

12

Vineyard, Craig M., Stephen J. Verzi, Conrad D. James, James B. Aimone i Gregory L. Heileman. "MapReduce SVM Game". Procedia Computer Science 53 (2015): 298–307. http://dx.doi.org/10.1016/j.procs.2015.07.307.

Pełny tekst źródła

Style APA, Harvard, Vancouver, ISO itp.

13

Sujitha, R., i B. Paramasivan. "Distributed Healthcare Framework Using MMSM-SVM and P-SVM Classification". Computers, Materials & Continua 70, nr 1 (2022): 1557–72. http://dx.doi.org/10.32604/cmc.2022.019323.

Pełny tekst źródła

Style APA, Harvard, Vancouver, ISO itp.

14

Xinxin Wang, i Jianlin Zhao. "Study of EEG based on SVM and SVM with EMD". Journal of Convergence Information Technology 7, nr 22 (31.12.2012): 227–35. http://dx.doi.org/10.4156/jcit.vol7.issue22.27.

Pełny tekst źródła

Style APA, Harvard, Vancouver, ISO itp.

15

Chelabi, M., T. Hacib, Z. Belli, M. R. Mekideche i Y. Le Bihan. "The combination of adaptive database SDM and multi-output SVM for eddy current testing". COMPEL: The International Journal for Computation and Mathematics in Electrical and Electronic Engineering 34, nr 6 (2.11.2015): 1731–39. http://dx.doi.org/10.1108/compel-12-2014-0348.

Pełny tekst źródła

Streszczenie:

Purpose – Eddy current testing (ECT) is a nondestructive testing method for the detection of flaws that uses electromagnetic induction to find defects in conductive materials. In this method, eddy currents are generated in a conductive material by a changing magnetic field. A defect is detected when there is a disruption in the flow of the eddy current. The purpose of this paper is to develop a new noniterative inversion methodology for detecting degradation (defect characterization) such as cracking, corrosion and erosion from the measurement of the impedance variations. Design/methodology/approach – The methodology is based on multi-output support vector machines (SVM) combined with the adaptive database schema design method (SDM). The forward problem was solved numerically using finite element method (FEM), with its accuracy experimentally verified. The multi-output SVM is a statistical learning method that has good generalization capability and learning performance. FEM is used to create the adaptive database required to train the multi-output SVM and the genetic algorithm is used to tune the parameters of multi-output SVM model. Findings – The results show the applicability of multi-output SVM to solve eddy current inverse problems instead of using traditional iterative inversion methods which can be very time-consuming. With the experimental results the authors demonstrate the accuracy which can be provided by the multi-output SVM technique. Practical implications – The work allows extending the capability of the experimentation ECT defect characterization system developed at LGEP. Originality/value – A new inversion method is developed and applied to ECT defect characterization. This new concept introduces multi-output SVM in the context of ECT. The real data together with estimated one obtained by multi-output SVM model are compared in order to evaluate the effectiveness of the developed technique.

Style APA, Harvard, Vancouver, ISO itp.

16

Zeng, Tan, Matsunaga i Shirai. "Generalization of Parameter Selection of SVM and LS-SVM for Regression". Machine Learning and Knowledge Extraction 1, nr 2 (19.06.2019): 745–55. http://dx.doi.org/10.3390/make1020043.

Pełny tekst źródła

Streszczenie:

A Support Vector Machine (SVM) for regression is a popular machine learning model that aims to solve nonlinear function approximation problems wherein explicit model equations are difficult to formulate. The performance of an SVM depends largely on the selection of its parameters. Choosing between an SVM that solves an optimization problem with inequality constrains and one that solves the least square of errors (LS-SVM) adds to the complexity. Various methods have been proposed for tuning parameters, but no article puts the SVM and LS-SVM side by side to discuss the issue using a large dataset from the real world, which could be problematic for existing parameter tuning methods. We investigated both the SVM and LS-SVM with an artificial dataset and a dataset of more than 200,000 points used for the reconstruction of the global surface ocean CO2 concentration. The results reveal that: (1) the two models are most sensitive to the parameter of the kernel function, which lies in a narrow range for scaled input data; (2) the optimal values of other parameters do not change much for different datasets; and (3) the LS-SVM performs better than the SVM in general. The LS-SVM is recommended, as it has less parameters to be tuned and yields a smaller bias. Nevertheless, the SVM has advantages of consuming less computer resources and taking less time to train. The results suggest initial parameter guesses for using the models.

Style APA, Harvard, Vancouver, ISO itp.

17

Cherkassky, Vladimir, i Yunqian Ma. "Practical selection of SVM parameters and noise estimation for SVM regression". Neural Networks 17, nr 1 (styczeń 2004): 113–26. http://dx.doi.org/10.1016/s0893-6080(03)00169-2.

Pełny tekst źródła

Style APA, Harvard, Vancouver, ISO itp.

18

DU, Jia-Zhi, Wei-Gang LU, Xiao-He WU, Jun-Yu DONG i Wang-Meng ZUO. "L-SVM: A radius-margin-based SVM algorithm with LogDet regularization". Expert Systems with Applications 102 (lipiec 2018): 113–25. http://dx.doi.org/10.1016/j.eswa.2018.02.006.

Pełny tekst źródła

Style APA, Harvard, Vancouver, ISO itp.

19

Gu, Qinghua, Yinxin Chang, Xinhong Li, Zhaozhao Chang i Zhidong Feng. "A novel F-SVM based on FOA for improving SVM performance". Expert Systems with Applications 165 (marzec 2021): 113713. http://dx.doi.org/10.1016/j.eswa.2020.113713.

Pełny tekst źródła

Style APA, Harvard, Vancouver, ISO itp.

20

Rodenhizer, Kara Anne E., i Katie M. Edwards. "The Impacts of Sexual Media Exposure on Adolescent and Emerging Adults’ Dating and Sexual Violence Attitudes and Behaviors: A Critical Review of the Literature". Trauma, Violence, & Abuse 20, nr 4 (13.07.2017): 439–52. http://dx.doi.org/10.1177/1524838017717745.

Pełny tekst źródła

Streszczenie:

Dating violence (DV) and sexual violence (SV) are widespread problems among adolescents and emerging adults. A growing body of literature demonstrates that exposure to sexually explicit media (SEM) and sexually violent media (SVM) may be risk factors for DV and SV. The purpose of this article is to provide a systematic and comprehensive literature review on the impact of exposure to SEM and SVM on DV and SV attitudes and behaviors. A total of 43 studies utilizing adolescent and emerging adult samples were reviewed, and collectively the findings suggest that (1) exposure to SEM and SVM is positively related to DV and SV myths and more accepting attitudes toward DV and SV; (2) exposure to SEM and SVM is positively related to actual and anticipated DV and SV victimization, perpetration, and bystander nonintervention; (3) SEM and SVM more strongly impact men’s DV and SV attitudes and behaviors than women’s DV and SV attitudes and behaviors; and (4) preexisting attitudes related to DV and SV and media preferences moderate the relationship between SEM and SVM exposure and DV and SV attitudes and behaviors. Future studies should strive to employ longitudinal and experimental designs, more closely examine the mediators and moderators of SEM and SVM exposure on DV and SV outcomes, focus on the impacts of SEM and SVM that extend beyond men’s use of violence against women, and examine the extent to which media literacy programs could be used independently or in conjunction with existing DV and SV prevention programs to enhance effectiveness of these programming efforts.

Style APA, Harvard, Vancouver, ISO itp.

21

Wu, Wei, Xin Liu, Min Xu, Jin-Rong Peng i Rudy Setiono. "A Hybrid SOM-SVM Approach for the Zebrafish Gene Expression Analysis". Genomics, Proteomics & Bioinformatics 3, nr 2 (2005): 84–93. http://dx.doi.org/10.1016/s1672-0229(05)03013-5.

Pełny tekst źródła

Style APA, Harvard, Vancouver, ISO itp.

22

Subha, R., i M. Pushpa Rani. "SVM based Iris Classification". International Journal of Computer Sciences and Engineering 6, nr 2 (28.02.2018): 321–23. http://dx.doi.org/10.26438/ijcse/v6i2.321323.

Pełny tekst źródła

Style APA, Harvard, Vancouver, ISO itp.

23

Henkin, Stanislav, i Robert D. McBane. "SVM Communications: Membership Spotlight". Vascular Medicine 27, nr 4 (29.07.2022): 418–20. http://dx.doi.org/10.1177/1358863x221112726.

Pełny tekst źródła

Style APA, Harvard, Vancouver, ISO itp.

24

Kadian-Dodov, Daniella, Carmel Celestin, Leben Tefera i Jeffrey Olin. "SVM Communications: Membership spotlight". Vascular Medicine 26, nr 4 (sierpień 2021): 475–77. http://dx.doi.org/10.1177/1358863x211024715.

Pełny tekst źródła

Style APA, Harvard, Vancouver, ISO itp.

25

WANG, YUNYUN, SONGCAN CHEN i HUI XUE. "STRUCTURE-EMBEDDED AUC-SVM". International Journal of Pattern Recognition and Artificial Intelligence 24, nr 05 (sierpień 2010): 667–90. http://dx.doi.org/10.1142/s0218001410008172.

Pełny tekst źródła

Streszczenie:

AUC-SVM directly maximizes the area under the ROC curve (AUC) through minimizing its hinge loss relaxation, and the decision function is determined by those support vector sample pairs playing the same roles as the support vector samples in SVM. Such a learning paradigm generally emphasizes more on the local discriminative information just associated with these support vectors whereas hardly takes the overall view of data into account, thereby it may incur loss of the global distribution information in data favorable for classification. Moreover, due to the high computational complexity of AUC-SVM induced by the large number of training sample pairs quadratic in the number of samples, sampling is usually adopted, incurring a further loss of the distribution information in data. In order to compensate the distribution information loss and simultaneously boost the AUC-SVM performance, in this paper, we develop a novel structure-embedded AUC-SVM (SAUC-SVM for short) through embedding the global structure information in the whole data into AUC-SVM. With such an embedding, the proposed SAUC-SVM incorporates the local discriminative information and global structure information in data into a uniform formulation and consequently guarantees better generalization performance. Comparative experiments on both synthetic and real datasets confirm its effectiveness.

Style APA, Harvard, Vancouver, ISO itp.

26

Valyon, József, i Gábor Horváth. "A generalised LS-SVM". IFAC Proceedings Volumes 36, nr 16 (wrzesień 2003): 801–6. http://dx.doi.org/10.1016/s1474-6670(17)34858-9.

Pełny tekst źródła

Style APA, Harvard, Vancouver, ISO itp.

27

Albers, Anne. "Get social with SVM". Vascular Medicine 21, nr 4 (25.07.2016): 408–9. http://dx.doi.org/10.1177/1358863x16652718.

Pełny tekst źródła

Style APA, Harvard, Vancouver, ISO itp.

28

Vaidya, Jaideep, Hwanjo Yu i Xiaoqian Jiang. "Privacy-preserving SVM classification". Knowledge and Information Systems 14, nr 2 (24.03.2007): 161–78. http://dx.doi.org/10.1007/s10115-007-0073-7.

Pełny tekst źródła

Style APA, Harvard, Vancouver, ISO itp.

29

Naofal Hakim, Mochamad Agusta, Adiwijaya Adiwijaya i Widi Astuti. "Comparative analysis of ReliefF-SVM and CFS-SVM for microarray data classification". International Journal of Electrical and Computer Engineering (IJECE) 11, nr 4 (1.08.2021): 3393. http://dx.doi.org/10.11591/ijece.v11i4.pp3393-3402.

Pełny tekst źródła

Streszczenie:

Cancer is one of the main causes of death in the world where the World Health Organization (WHO) recognized cancer as among the top causes of death in 2018. Thus, detecting cancer symptoms is paramount in order to cure and subsequently reduce the casualties due to cancer disease. Many studies have been developed data mining approaches to detect symptoms of cancer through a classifying human gene data expression. One popular approach is using microarray data based on DNA. However, DNA microarray data has many dimensions that can have a detrimental effect on the accuracy of classification. Therefore, before performing classification, a feature selection technique must be used to eliminate features that do not have important information to support the classification process. The feature selection techniques used were ReliefF and correlation-based feature selection (CFS) and a classification technique used in this study is support vector machine (SVM). Several testing schemes were applied in this analysis to compare the performance of ReliefF and CFS with SVM. It showed that the ReliefF outperformed compared with CFS as microarray data classification approach.

Style APA, Harvard, Vancouver, ISO itp.

30

Zhang, R., i J. Ma. "An improved SVM method P‐SVM for classification of remotely sensed data". International Journal of Remote Sensing 29, nr 20 (20.09.2008): 6029–36. http://dx.doi.org/10.1080/01431160802220151.

Pełny tekst źródła

Style APA, Harvard, Vancouver, ISO itp.

31

Xu, Dehong, Bo Feng, Rui Li, Kazuaki Mino i Hidetoshi Umida. "A Zero Voltage Switching SVM (ZVS–SVM) Controlled Three-Phase Boost Rectifier". IEEE Transactions on Power Electronics 22, nr 3 (maj 2007): 978–86. http://dx.doi.org/10.1109/tpel.2007.897006.

Pełny tekst źródła

Style APA, Harvard, Vancouver, ISO itp.

32

Nie, Feiping, Wei Zhu i Xuelong Li. "Decision Tree SVM: An extension of linear SVM for non-linear classification". Neurocomputing 401 (sierpień 2020): 153–59. http://dx.doi.org/10.1016/j.neucom.2019.10.051.

Pełny tekst źródła

Style APA, Harvard, Vancouver, ISO itp.

33

Wu, Xiaohe, Wangmeng Zuo, Liang Lin, Wei Jia i David Zhang. "F-SVM: Combination of Feature Transformation and SVM Learning via Convex Relaxation". IEEE Transactions on Neural Networks and Learning Systems 29, nr 11 (listopad 2018): 5185–99. http://dx.doi.org/10.1109/tnnls.2018.2791507.

Pełny tekst źródła

Style APA, Harvard, Vancouver, ISO itp.

34

ZERGAT, KAWTHAR YASMINE, i ABDERRAHMANE AMROUCHE. "SVM AGAINST GMM/SVM FOR DIALECT INFLUENCE ON AUTOMATIC SPEAKER RECOGNITION TASK". International Journal of Computational Intelligence and Applications 13, nr 02 (czerwiec 2014): 1450012. http://dx.doi.org/10.1142/s1469026814500126.

Pełny tekst źródła

Streszczenie:

A big deal for current research on automatic speaker recognition is the effectiveness of the speaker modeling techniques for the talkers, because they have their own speaking style, depending on their specific accents and dialects. This paper investigates on the influence of the dialect and the size of database on the text independent speaker verification task using the SVM and the hybrid GMM/SVM speaker modeling. The Principal Component Analysis (PCA) technique is used in the front-end part of the speaker recognition system, in order to extract the most representative features. Experimental results show that the size of database has an important impact on the SVM and GMM/SVM based speaker verification performances, while the dialect has no significant effect. Applying PCA dimensionality reduction improves the recognition accuracy for both SVM and GMM/SVM based recognition systems. However, it did not give an obvious observation about the dialect effect.

Style APA, Harvard, Vancouver, ISO itp.

35

Samantaray, Sandeep, Abinash Sahoo i Dillip K. Ghose. "Assessment of Sediment Load Concentration Using SVM, SVM-FFA and PSR-SVM-FFA in Arid Watershed, India: A Case Study". KSCE Journal of Civil Engineering 24, nr 6 (1.05.2020): 1944–57. http://dx.doi.org/10.1007/s12205-020-1889-x.

Pełny tekst źródła

Style APA, Harvard, Vancouver, ISO itp.

36

Huang, Mei-Ling, Yung-Hsiang Hung, W. M. Lee, R. K. Li i Bo-Ru Jiang. "SVM-RFE Based Feature Selection and Taguchi Parameters Optimization for Multiclass SVM Classifier". Scientific World Journal 2014 (2014): 1–10. http://dx.doi.org/10.1155/2014/795624.

Pełny tekst źródła

Streszczenie:

Recently, support vector machine (SVM) has excellent performance on classification and prediction and is widely used on disease diagnosis or medical assistance. However, SVM only functions well on two-group classification problems. This study combines feature selection and SVM recursive feature elimination (SVM-RFE) to investigate the classification accuracy of multiclass problems for Dermatology and Zoo databases. Dermatology dataset contains 33 feature variables, 1 class variable, and 366 testing instances; and the Zoo dataset contains 16 feature variables, 1 class variable, and 101 testing instances. The feature variables in the two datasets were sorted in descending order by explanatory power, and different feature sets were selected by SVM-RFE to explore classification accuracy. Meanwhile, Taguchi method was jointly combined with SVM classifier in order to optimize parametersCandγto increase classification accuracy for multiclass classification. The experimental results show that the classification accuracy can be more than 95% after SVM-RFE feature selection and Taguchi parameter optimization for Dermatology and Zoo databases.

Style APA, Harvard, Vancouver, ISO itp.

37

Rahmanul Hoque, Masum Billah, Amit Debnath, S. M. Saokat Hossain i Numair Bin Sharif. "Heart Disease Prediction using SVM". International Journal of Science and Research Archive 11, nr 2 (30.03.2024): 412–20. http://dx.doi.org/10.30574/ijsra.2024.11.2.0435.

Pełny tekst źródła

Streszczenie:

Diagnosing and predicting the outcome of cardiovascular disease are essential tasks in medicine that help ensure patients receive accurate classification and treatment from cardiologists. The use of machine learning in the healthcare sector has grown due to its ability to identify patterns in data. By applying machine learning techniques to classify the presence of cardiovascular diseases, it's possible to decrease the rate of misdiagnosis. This study aims to create a model capable of accurately forecasting cardiovascular diseases to minimize the deaths associated with these conditions. In this paper, two types of SVM model such as linear SVM and polynomial SVM is used. Accuracy, precision, recall and F1 score has been evaluated for comparing linear SVM and polynomial SVM. Polynomial SVM provides better accuracy than linear SVM.

Style APA, Harvard, Vancouver, ISO itp.

38

He, Wei, i Jie Xiong. "Application of Intelligent Data Mining Method for Traffic Forecasting". Applied Mechanics and Materials 84-85 (sierpień 2011): 405–9. http://dx.doi.org/10.4028/www.scientific.net/amm.84-85.405.

Pełny tekst źródła

Streszczenie:

Potential knowledge useful for traffic management optimization is hidden in a huge amount of data. Previous works use the prior data pattern labels to train the artificial neural network to attain the intelligent data mining models. The performance of the models suffers from the experts’ experience. To relieve the impact of the human factor, a new hybrid intelligent data mining model is proposed in this work based on self-organizing map (SOM) and support vector machine (SVM). The SOM was firstly used to capture the clustering information of the database through an unsupervised manner. Then the identified samples were treated as input to train the SVM. To optimize the SVM model, the particle swarm optimization (PSO) algorithm was employed to tune the SVM parameters and hence the satisfactory SVM data mining model was obtained. 2000 practical data sets from the Intelligent Transportation Systems (ITS) were applied to the validation of the proposed mining model. The analysis results show that the proposed method can extract the underlying rules of the testing data and can predict the future traffic state with the accuracy beyond 97%. Hence, the new SOM-PSO-SVM data mining model can provide practical application for the ITS.

Style APA, Harvard, Vancouver, ISO itp.

39

Emilia Ayu Wijayanti, Tania Rahmadanti i Ultach Enri. "Perbandingan Algoritma SVM dan SVM Berbasis Particle Swarm Optimization Pada Klasifikasi Beras Mekongga". Generation Journal 5, nr 2 (21.07.2021): 102–8. http://dx.doi.org/10.29407/gj.v5i2.16075.

Pełny tekst źródła

Streszczenie:

Rice is the most important staple food in Indonesia. There are various types of varieties available, one of them is Inpari Mekongga variety. In Karawang, Mekongga rice type is the most popular and superior compared to others. However, this type of rice is often mixed with the other types because there are too many varieties and various other problems. Classifying varieties of rice types can be done to identify the types of rice. The classification of rice varieties in this research is divided into 2 classes, Mekongga and not Mekongga. The method that used in this reserach is Support Vector Machine (SVM) and Particle Swarm Optimatizon (PSO). SVM method was chosen because it basically handles the classification of two classes. Meanwhile, PSO method used to optimize the accuracy level of the SVM method. Combination from the two methods is very well used in classification data because it can increase the level of accuracy better. The purpose of this reserach is compare the accuracy of the 2 methods that used. The results from research is mekongga rice classification with Support Vector Machine has accuracy value 46.67% and AUC value 0.475. Meanwhile, using Support Vector Machine based on Particle Swarm Optimization (PSO) can help improve the classification of this mekongga rice with accuracy value 70.83% and AUC value 0.671.

Style APA, Harvard, Vancouver, ISO itp.

40

Chen, Gecheng, i Zhiqiang Ge. "SVM-tree and SVM-forest algorithms for imbalanced fault classification in industrial processes". IFAC Journal of Systems and Control 8 (czerwiec 2019): 100052. http://dx.doi.org/10.1016/j.ifacsc.2019.100052.

Pełny tekst źródła

Style APA, Harvard, Vancouver, ISO itp.

41

Ma, Junshui, Ashok Krishnamurthy i Stanley Ahalt. "SVM training with duplicated samples and its application in SVM-based ensemble methods". Neurocomputing 61 (październik 2004): 455–59. http://dx.doi.org/10.1016/j.neucom.2004.04.004.

Pełny tekst źródła

Style APA, Harvard, Vancouver, ISO itp.

42

Maldonado, Sebastian, Jose Merigo i Jaime Miranda. "IOWA-SVM: A Density-Based Weighting Strategy for SVM Classification via OWA Operators". IEEE Transactions on Fuzzy Systems 28, nr 9 (wrzesień 2020): 2143–50. http://dx.doi.org/10.1109/tfuzz.2019.2930942.

Pełny tekst źródła

Style APA, Harvard, Vancouver, ISO itp.

43

JU, WEN, i H. D. CHENG. "A NOVEL NEUTROSOPHIC LOGIC SVM (N-SVM) AND ITS APPLICATION TO IMAGE CATEGORIZATION". New Mathematics and Natural Computation 09, nr 01 (marzec 2013): 27–42. http://dx.doi.org/10.1142/s1793005713500038.

Pełny tekst źródła

Streszczenie:

Neutrosophic logic is a relatively new logic that is a generalization of fuzzy logic. In this paper, for the first time, neutrosophic logic is applied to the field of classifiers where a support vector machine (SVM) is adopted as the example to validate its feasibility and effectiveness. The proposed neutrosophic set is integrated into a reformulated SVM, and the performance of the obtained classifier N-SVM is evaluated under a region-based image categorization system. Images are first segmented by a hierarchical two-stage self-organizing map (HSOM) using color and texture features. A novel approach is proposed to select the training samples of HSOM based on homogeneity properties. A diverse density support vector machine (DD-SVM) framework is then applied to viewing an image as a bag of instances corresponding to the regions obtained from image segmentation. Each bag is mapped to a point in the new bag space, and the categorization is transformed to a classification problem. Then, the proposed N-SVM is used as the classifier in the new bag space. N-SVM treats samples differently according to the weighting function, and it helps to reduce the effects of outliers. Experimental results have demonstrated the validity and effectiveness of the proposed method which may find wide applications in the related areas.

Style APA, Harvard, Vancouver, ISO itp.

44

Awalullaili, Fithroh Oktavi, Dwi Ispriyanti i Tatik Widiharih. "KLASIFIKASI PENYAKIT HIPERTENSI MENGGUNAKAN METODE SVM GRID SEARCH DAN SVM GENETIC ALGORITHM (GA)". Jurnal Gaussian 11, nr 4 (12.12.2022): 488–98. http://dx.doi.org/10.14710/j.gauss.11.4.488-498.

Pełny tekst źródła

Streszczenie:

Hypertension is an abnormally high pressure that occurs inside the arteries. Hypertension increased by 8.3% from 2013 based on health research in 2018. Some of the factors that cause hypertension include gender, age, salt consumption, cigarette consumption, cholesterol levels and a family history of hypertension. The data in this study are data on normal and hypertensive patients at the Padangsari Health Center for the period of July – December 2021. This study will classify blood pressure with the aim of obtaining the results of the accuracy of the classification of the methods used. The method used in this study is a support vector machine (SVM). SVM is a well-known algorithm, producing optimal solutions to classification problems. SVM uses kernel functions for separable nonlinear data. The displacement kernels used in this study are linear and RBF. SVM has the disadvantage of determining the best parameters, to overcome these weaknesses developed the method of finding the best parameters. The search for the parameters of this study used grid search and genetic algorithm (GA). Grid search has the advantage of producing parameters that are close to the optimal value, while GA has the advantage of being easy to find global optimum values. This study will compare the classification results of the SVM grid search and SVM GA methods. The results of this study obtained the method that has the best accuracy, namely SVM grid search using a radial base function (RBF) kernel with an accuracy of 89.22%.

Style APA, Harvard, Vancouver, ISO itp.

45

Alshamlan, Hala M., Ghada H. Badr i Yousef A. Alohali. "ABC-SVM: Artificial Bee Colony and SVM Method for Microarray Gene Selection and Multi Class Cancer Classification". International Journal of Machine Learning and Computing 6, nr 3 (czerwiec 2016): 184–90. http://dx.doi.org/10.18178/ijmlc.2016.6.3.596.

Pełny tekst źródła

Style APA, Harvard, Vancouver, ISO itp.

46

Liu, Bingchun, Mingzhao Lai, Jheng-Long Wu, Chuanchuan Fu i Arihant Binaykia. "Patent analysis and classification prediction of biomedicine industry: SOM-KPCA-SVM model". Multimedia Tools and Applications 79, nr 15-16 (12.03.2019): 10177–97. http://dx.doi.org/10.1007/s11042-019-7422-x.

Pełny tekst źródła

Style APA, Harvard, Vancouver, ISO itp.

47

Lim, Chungsoo, i Joon-Hyuk Chang. "Efficient implementation techniques of an SVM-based speech/music classifier in SMV". Multimedia Tools and Applications 74, nr 15 (1.02.2014): 5375–400. http://dx.doi.org/10.1007/s11042-014-1859-8.

Pełny tekst źródła

Style APA, Harvard, Vancouver, ISO itp.

48

Wei, Chen, Xibo Yuan, Yonglei Zhang i Xiaojie Wu. "A Generic Multi-Level SVM Scheme Based on Two-Level SVM for n-Level Converters". Energies 13, nr 9 (30.04.2020): 2143. http://dx.doi.org/10.3390/en13092143.

Pełny tekst źródła

Streszczenie:

Multi-level converters are widely used in various industrial applications. Among various space vector modulation (SVM) schemes, the multi-level SVM scheme based on two-level space vector pulse width modulation (SVPWM) is recognised as a simplified multi-level SVM scheme, which can reduce the computation complexity. However, this scheme is still complicated when the number of the voltage levels is large. This paper proposes a modified SVM scheme that can further simplify the multi-level SVM scheme based on two-level SVPWM. The proposed SVM scheme can directly determine the two-level hexagon where the reference voltage vector is located by calculating a simple formula. The whole modulation process can be completed by only three steps. Meanwhile, the proposed method is generic for any n-level converter without adding much calculation, which greatly simplifies the modulation process. Experimental results have been provided, which verify the effectiveness and generality of the proposed SVM scheme for two types of multi-level converters.

Style APA, Harvard, Vancouver, ISO itp.

49

Choi, Ha Na, i Dong Hoon Lim. "Bankruptcy prediction using ensemble SVM model". Journal of the Korean Data and Information Science Society 24, nr 6 (30.11.2013): 1113–25. http://dx.doi.org/10.7465/jkdi.2013.24.6.1113.

Pełny tekst źródła

Style APA, Harvard, Vancouver, ISO itp.

50

Park, Sun-Mi, i Ku-Jin Kim. "PCA-SVM Based Vehicle Color Recognition". KIPS Transactions:PartB 15B, nr 4 (29.08.2008): 285–92. http://dx.doi.org/10.3745/kipstb.2008.15-b.4.285.

Pełny tekst źródła

Style APA, Harvard, Vancouver, ISO itp.

Oferujemy zniżki na wszystkie plany premium dla autorów, których prace zostały uwzględnione w tematycznych zestawieniach literatury. Skontaktuj się z nami, aby uzyskać unikalny kod promocyjny!