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205 results for “Support Vector”
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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 titleAn Implementation of Support Vector Machine on the Multi-Label Classification of English-Translated Quranic VersesSatrio Adi Prabowo, Adiwijaya, Mohamad Syahrul Mubarok et al.One of the attempts to understand the meaning and content of the Quran, the central religious text of Islam, is the topic classification of Quranic verses. Verse topic classification aims to help the reader, so he can easily and quickly find information or knowledge contained in the Quran. In this paper, we build a classification model for the topics of … …Journal of Computer Science, Vol. 15, Issue 12 · 19 Dec 2019 · 7,783 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 titleMulti-Phase Support Vector Regression Soft Sensor for Online Product Quality Prediction in Glutamate Fermentation ProcessRongjian Zheng, Feng PanGlutamate fermentation is inherently nonlinear, multi-phase and an aerobic fermentation process. As long measurement delays and expensive apparatus cost, on-line measurement of the product concentration is not necessarily available. The present fermentation process monitoring and quality prediction involve manual interpretation of highly informative, however, the concentrations of substrates, biomass and products are only low frequency off-line measurements. In this paper, … …American Journal of Biochemistry and Biotechnology, Vol. 13, Issue 2 · 6 Jun 2017 · 8,067 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 titleA Soft Sensor Modelling of Biomass Concentration during Fermentation using Accurate Incremental Online v-Support Vector Regression Learning AlgorithmBinjie Gu, Feng PanIn order to model real fermentation process, a soft sensor modelling of biomass concentration during fermentation using accurate incremental online ν-Support Vector Regression (ν-SVR) learning algorithm was proposed. Firstly, an accurate incremental online ν-SVR learning algorithm was proposed. This algorithm solved the two complications introduced in the dual problem based on the equivalent formulation of ν-SVR. Moreover, it addressed the … …American Journal of Biochemistry and Biotechnology, Vol. 11, Issue 3 · 8 Aug 2015 · 7,327 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