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185 results for “Support vector machine”
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Research ArticleOpen accessPhrase in the titleEpsilon-Insensitive Primal Loss With Support Vector Machine for Robust Cotton Leaf Disease ClassificationPavana Kumar Eramachetty Dhanajayalu, Malathi Sivasamy, Chitveli Siva Balaji YadavCotton diseases significantly reduce both yield and quality of crops, making early and accurate identification of the disease crucial for effective prevention and control. However, achieving a balance between lightweight models and precise classification of cotton diseases remains challenging. This difficulty arises primarily from the dispersed nature of disease symptoms and interference from noisy backgrounds, which complicate the detection process. … …Journal of Computer Science, Vol. 22, Issue 6 · 5 Aug 2026 · 755 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleAn Ensemble of Gaussian Mixture Model and Support Vector Machines for Network Intrusion DetectionOlujimi Daniel Alao, Sheriff Alimi, Shade Oluwakemi Kuyoro et al.NetworkIntrusion Detection Systems (NIDS) can protect computer networks and computersystems by detecting abnormal network packets and taking agreed action plans,such as notifying an administrator or rejecting the network packets. In this study,the aim is the implementation of NIDS with improved performance using anensemble of Support Vector Machines (SVMs) and the Gaussian Mixture Model(GMM). Four SVMs with Radial Basis Function (RBF), … …Journal of Computer Science, Vol. 18, Issue 9 · 21 Sep 2022 · 6,114 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleEnhanced Support Vector Machine based on Metaheuristic Search for Multiclass ProblemsAbdullah Saeed Ghareb, Mohammed Hamid Afif, Abdel-Rahman Hedar et al.Machine learning is an important field of artificial intelligent researches and it highly growing for real intelligent applications systems that relate brain computer interface to human brain activities. Support Vector Machine (SVM) is a popular machine learning approach, which can be used for pattern recognition, prediction and classification with many diverse applications. However, the SVM has many parameters, which have … …Journal of Computer Science, Vol. 16, Issue 7 · 9 Jul 2020 · 6,906 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleA Comparison between Conditional Random Field and Structured Support Vector Machine for Arabic Named Entity RecognitionMarwa Muhammad, Muhammad Rohaim, Alaa Hamouda, Salah Abdel-MageidThe Named Entity Recognition (NER) is an integrated task in many NLP applications such as machine translation, Information extraction and question answering. Arabic is one of the authorised spoken languages in the united nation. Currently, there is much Arabic information on the internet, so, nowadays the need for tools which process this information becomes significant. In this study, we have … …Journal of Computer Science, Vol. 16, Issue 1 · 30 Jan 2020 · 8,113 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleCost-based Reweighting for Principal Lq Support Vector Machines for Sufficient Dimension ReductionAndreas ArtemiouIn this work we try to address the imbalance of the number of points which naturally occurs when slicing the response in Sufficient Dimension Reduction methods (SDR). Specifically, some recently proposed support vector machine based (SVM-based) methodology suffers a lot more due to the properties of the SVM algorithm. We target a recently proposed algorithm called Principal LqSVM and we … …Journal of Mathematics and Statistics, Vol. 15, Issue 1 · 5 Sep 2019 · 7,254 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleEvaluation of Customer Behaviour Irregularities in Cameroon Electricity Network using Support Vector MachineLekini Nkodo Claude Bernard, Ndzana Benoît, Oumarou HamandjodaNon-Technical Losses (NTLs) in the Cameroonians electricity network are approximately 30 to 40% of production and are estimated at several billion CFA francs per year for National Electricity Company (ENEO); Hence the importance of finding effective solutions to fight against these losses. The purpose of this work was to develop a tool for the fraud detection for Cameroon National Electricity … …American Journal of Engineering and Applied Sciences, Vol. 10, Issue 1 · 6 Jan 2017 · 7,544 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleDAILY CRUDE OIL PRICE FORECASTING MODEL USING ARIMA, GENERALIZED AUTOREGRESSIVE CONDITIONAL HETEROSCEDASTIC AND SUPPORT VECTOR MACHINESRana Abdullah Ahmed, Ani Bin ShabriCrude oil price forecasting is gaining increased interest globally. This interest is due mainly to the economic value attached to the product. For this reason, new forecasting methods are proposed in the literature. This paper proposes a novel technique for forecasting crude oil price based on Support Vector Machines (SVM). The study adopts the data on crude oil price of … …American Journal of Applied Sciences, Vol. 11, Issue 3 · 11 Jan 2014 · 8,725 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleIMPROVING INDEPENDENT COMPONENT ANALYSIS USING SUPPORT VECTOR MACHINES FOR MULTIMODAL IMAGE FUSIOND. Egfin Nirmala, A. Bibin Sam Paul, V. VaidehiThe objective of this study is to combine multiple images of a scene acquired by different sensors to create a new image with all important information from the input images. Recent studies show that bases trained using Independent Component Analysis (ICA) is effective in multisensor fusion and has improved performance over traditional wavelet approaches. In the ICA based fusion, the … …Journal of Computer Science, Vol. 9, Issue 9 · 6 Aug 2013 · 7,272 accessesView PDFCite
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 PDFCite
Research ArticleOpen accessPhrase in the titleSecond-Order Statistical Approach for Digital Modulation Scheme Classification in Cognitive Radio Using Support Vector Machine and K-Nearest Neighbor ClassifierS. Ravi, R. KannanCognitive radio systems require detection of different signals for communication. In this study, an approach for multiclass signal classification based on second-order statistical feature is proposed. The proposed system is designed to recognize three different digital modulation schemes such as PAM, 32QAM and 64QAM. The signal classification is achieved by extracting the 2nd order cumulants of the real and imaginary … …Journal of Computer Science, Vol. 9, Issue 2 · 11 Apr 2013 · 6,732 accessesView PDFCite