72 results for “Support Vector Machine Algorithm”

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Research ArticleOpen accessPhrase in the titleA NOVEL MULTICLASS SUPPORT VECTOR MACHINE ALGORITHM USING MEAN REVERSION AND COEFFICIENT OF VARIANCEBhusana Premanode, Jumlong Vongprasert, Nop Sopipan, Christofer ToumazouInaccuracy of a kernel function used in Support Vector Machine (SVM) can be found when simulated with nonlinear and stationary datasets. To minimise the error, we propose a new multiclass SVM model using mean reversion and coefficient of variance algorithm to partition and classify imbalance in datasets. By introducing a series of test statistic, simulations of the proposed algorithm outperformed … …Journal of Mathematics and Statistics, Vol. 9, Issue 3 · 31 Jul 2013 · 6,932 accessesView PDF Cite

Research ArticleOpen accessEvery word in the titleAn Adaptive Region Growing Algorithm with Support Vector Machine Classifier for Tuberculosis Cavity IdentificationK. Meenakshi Sundaram, C. S. RavichandranThe major world health menace is Tuberculosis (TB) that has the effect on one-third of the global population and millions of new infections are occurring every year. The cavities in the upper lung zone are a strong indicator that the disease has developed into a highly contagious state. The study includes 52 Chest X-ray images with Tuberculosis and 43 Chest … …American Journal of Applied Sciences, Vol. 10, Issue 12 · 29 Oct 2013 · 7,067 accessesView PDF Cite

Research ArticleOpen accessIn the keywordsDefect Classification of Reinforced Concrete Structures with Nondestructive Tests Using Statistical and Machine Learning MethodsSajjad Sayyar-Roudsari, Armaghan Shalbaftabar, Farshid Damirchilo et al.In this study, twelve reinforced concrete beams were constructed, each with specified dimensions and initial compressive strength. The beams were divided into four groups: A control group without any defect, a void group featuring a centrally located void, a corrosion group and a debonding group. The impact echo test was used for nondestructive testing, gathering data on compressive and shear … …American Journal of Engineering and Applied Sciences, Vol. 17, Issue 3 · 11 Jun 2024 · 5,258 accessesView PDF Cite

Research ArticleOpen accessIn the keywordsAn Improved Approach for Topic Ontology Based Categorization of Blogs Using Support Vector MachineV. Subramaniyaswamy, S. Chenthur PandianProblem statement: Information search, collection and categorization from the blogosphere are still one of the important issues to be resolved. Mainly, the blogs assist the variety of interesting and useful information. Because of its increasing growth, blogs can not be categorized effectively. Therefore it is difficult to find relevant topics from the blogs. Hence blogs need to be categorized topically … …Journal of Computer Science, Vol. 8, Issue 2 · 29 Nov 2011 · 7,963 accessesView PDF Cite

Research ArticleOpen accessIn the keywordsFeature Subset Selection for Hot Method Prediction using Genetic Algorithm wrapped with Support Vector MachinesSandra Johnson, Valli ShanmugamProblem statement: All compilers have simple profiling-based heuristics to identify and predict program hot methods and also to make optimization decisions. The major challenge in the profile-based optimization is addressing the problem of overhead. The aim of this work is to perform feature subset selection using Genetic Algorithms (GA) to improve and refine the machine learnt static hot method predictive … …Journal of Computer Science, Vol. 7, Issue 5 · 7 May 2011 · 7,234 accessesView PDF Cite

Research ArticleOpen accessIn the keywordsToward Intelligent Evaluation of Digital Public Services: Evidence from Indonesia’s SIM Online PlatformEvaristus Didik Madyatmadja, Ricky Kosasih, Najla Aurelia Evanthe et al.This investigation examines more than 65,000 user evaluations from the Google Play Store concerning sentiment toward the Digital Korlantas POLRI application. Reviews were systematically processed and categorized through Naïve Bayes, Support Vector Machine, and Random Forest classifiers, thereby highlighting the perceived strengths and weaknesses of the platform. Among the tested models, Naïve Bayes outperformed the others, yielding the greatest accuracy, … …Journal of Computer Science, Vol. 22, Issue 6 · 15 Jun 2026 · 1,345 accessesView PDF Cite

Research ArticleOpen accessIn the keywordsSmart and Secure Anomaly Detection in IoT Using Quantum Inspired Kernel Ensemble LearningAbrar M. AlajlanThe exponential growth of the Internet of Things networks has greatly increased the attack surface for cyber threats, necessitating the use of strong and perceptive anomaly detection systems. Traditional intrusion detection systems often struggle with high false alarm rates, limited generalization, and inefficiency in processing high-dimensional heterogeneous IoT data. To address this issue, a novel Hybrid Quantum-Enhanced Kernel Ensemble Learning … …Journal of Computer Science, Vol. 22, Issue 3 · 12 Mar 2026 · 1,762 accessesView PDF Cite

Research ArticleOpen accessIn the keywordsSupport Vector Machine Based Red Palm Weevil (Rynchophorus Ferrugineous, Olivier) Recognition SystemGhulam Mubashar Hassan, Saleh Mufleh Al-SaqerProblem statement: Red palm weevil (Rynchophorus Ferrugineous, Oliveir) is an insect which threatens the existence of palm trees. The proposed research is to develop a RPW identification system using Support Vector Machine method. The problem is to extract image features from an image and using SVM to find out the existence of RPW in an image. Approach: Images are snapped … …American Journal of Agricultural and Biological Sciences, Vol. 7, Issue 1 · 24 Jan 2012 · 7,734 accessesView PDF Cite

Research ArticleOpen accessIn the abstractPandemic Analysis and Preparedness Using a Three Layer Machine Learning ApproachArtika Singh, Manisha JailiaOutbreak analysis provides research-based information and data to enable scientific decision-making to manage an effective response to a pandemic. Pandemic analysis has its own set of challenges, such as limited data, the need for real time analysis, and the complexity of outbreak patterns. This study proposes a hybrid approach to manage such a spread through a 3-layer machine learning-based outbreak … …Journal of Computer Science, Vol. 22, Issue 11 · 15 Oct 2026 · 614 accessesView PDF Cite

Research ArticleOpen accessIn the abstractAssessing Supervised Classification Algorithms for Mangrove Detection and Differentiation from Other Forest Types in Paiton District, Probolinggo RegencyKaruniawan Puji Wicaksono, Fathor Rohman, Yasushi MitsudaRemote sensing provides an effective approach for monitoring forest cover dynamics, yet distinguishing mangroves from other forest types remains challenging in heterogeneous coastal landscapes. This study compares six supervised classification algorithms: Linear Discriminant Analysis (LDA), Quadratic Discriminant Analysis (QDA), Mixture Discriminant Analysis (MDA), Support Vector Machine (SVM), Random Forest (RF), and eXtreme Gradient Boosting (XGBoost) for mangrove detection in Paiton, … …OnLine Journal of Biological Sciences, Vol. 26, Issue 3 · 1 Sep 2026 · 844 accessesView PDF Cite