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Rao-SVM machine learning algorithm for intrusion detection system by Abd, Shamis N., Alsajri, Mohammad, Ibraheem, Hind Raad

“…The prominent intrusion machine-learning dataset, UNSW-NB15, was used for the experiments and the results showed that Rao-SVM reached 92.5% accuracy on the UNSW-NB15 dataset.…”
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Abnormalities and fraud electric meter detection using hybrid support vector machine & genetic algorithm by Yap K.S., Abidin I.Z., Ahmad A.R., Hussien Z.F., Pok H.L., Ismail F.I., Mohamad A.M.

“…This paper presents an intelligent system to reduce Non Technical Loss (NTL) using hybrid Support Vector Machine (SVM) and Genetic Algorithm (GA). …”

Extending the decomposition algorithm for support vector machines training by Zaki, N,M., Deris, S., Chin, K.K.

“…Using a conventional optimizer to train SVM is not the ideal solution. …”
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Development of classification algorithms of human gait by Koh, Chee Hong

“…Two classification algorithms were developed: Support Vector Machine (SVM) classification algorithm and Artifical Neural Network (ANN). …”
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Forest mapping in Peninsular Malaysia using Random Forest and Support Vector Machine Classifiers on Google Earth Engine by Farah Nuralissa Muhammad, Lam, Kuok Choy

“…The accuracy assessment test using the Kappa coefficient resulted in a value of 0.7893 for the RF algorithm and 0.6328 for the SVM algorithm for the year 2010. …”
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Hand gesture recognition for autism diagnosis using Support Vector Machine (SVM) Algorithm / Muhammad Asyraf Mohamad Zain by Mohamad Zain, Muhammad Asyraf

“…To counter this problem, a system has been proposed to detect the hand gesture using one of the machine learning technique which is Support Vector Machine (SVM) Algorithm. …”
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Novel approach for IP-PBX denial of service intrusion detection using support vector machine algorithm by Jama, Abdirisaq M., Khalifa, Othman Omran, Subramaniam, Nantha Kumar

“…In this research, Support Vector Machine (SVM) machine learning detection & prevention algorithm were developed to detect this type of attacks Two other techniques were benchmarked decision tree and Naïve Bayes. …”
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Improved hybrid teaching learning based optimization-jaya and support vector machine for intrusion detection systems by Mohammad Khamees Khaleel, Alsajri

“…Most of the currently existing intrusion detection systems (IDS) use machine learning algorithms to detect network intrusion. …”
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Diagnosis and treatment recommender system for myocardial infarction using decision tree and Support Vector Machines (SVM) / Wan Marzuqiamrin Wan Mansor by Wan Mansor, Wan Marzuqiamrin

“…This project presents the development process of the prototype for diagnosis and treatment recommender system for myocardial infarction using decision tree and support vector machine (SVM) algorithms. …”
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Prediction of COVID-19 outbreak using Support Vector Machine / Muhammad Qayyum Mohd Azman by Mohd Azman, Muhammad Qayyum

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A Knowledge Management System for Assessing Lecturer Competence in Indonesian Higher Educational Institutions by Syaripudin, Undang

“…Lecturer competency measurement is carried out by first checking employee status using the SVM algorithm with an accuracy value of 72.28%, then using a hybrid SVM and PSO algorithm with an accuracy value of 100%. …”
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SVM modelling of agarwood oil quality grading using radial basis function (RBF) and sequential minimal optimization (SMO) learning algorithms by Muhammad Haziq Haikal, Hisham, Nurlaila, Ismail, Nor Azah, Mohd Ali, Saiful Nizam, Tajuddin, Mohd Nasir, Taib

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A hybrid intrusion detection system based on different machine learning algorithms by Atefi, Kayvan, Yahya, Saadiah, Dak, Ahmad Yusri, Atefi, Arash

“…There are numerous study in intrusion detection system (IDS) especially with Genetic algorithms (GA) and Support Vector Machine (SVM) but most of them did not get the potential of hybrid SVM using GA. …”
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Direct approach for mining association rules from structured XML data by Abazeed, Ashraf Riad

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Lightning fault classification for transmission line using support vector machine by Asman, Saidatul Habsah, Ab Aziz, Nur Fadilah, Ab Kadir, Mohd Zainal Abidin, Ungku Amirulddin, Ungku Anisa, Roslan, Nurzanariah, Elsanabary, Ahmed

“…The classification performance of the developed algorithms was evaluated using confusion matrix. …”
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Spectral discrimination and index development of roofing materials and conditions using field spectroscopy and worldview-3 satellite image by Samsudin, Sarah Hanim

“…Three feature selection algorithms of Genetic Algorithm (GA), Support Vector Machine (SVM) and Random Forest (RF) were used to select the most significant wavelengths since the algorithms works well with large size of data and widely applied for feature selection of hyperspectral remote sensing data. …”
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Improving hand written digit recognition using hybrid feature selection algorithm by Wong, Khye Mun

“…The result showed that the hybrid mRMR+SVM-RFE was better than both the sole SVM-mRMR and the sole SVM-RFE approaches in the sense that the hybrid approach achieved higher classification accuracy by using a smaller amount of features.…”
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Improvement of land cover mapping using Sentinel 2 and Landsat 8 imageries via non-parametric classification by Myaser, Jwan

“…Nevertheless, AC is not required for LCM if the original multi-spectral image is used. The last phase involves developing a new fusion algorithm using SVM and Fuzzy K-Means Clustering (FKM) algorithms for Sentinel 2 data to enhance LCM accuracy. …”
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Implementation of Space Vector Modulation for Voltage Source Inverter by Sanusi, Syamim, Ibrahim, Zulkifli, Jidin , Auzani, JOPRI, MOHD HATTA, Abdul Karim, Kasrul, Othman, Md Nazri

“…This paper presents a development of a voltage source inverter (VSI) for electrical drive applications based on Space Vector Modulation (SVM) technique and the SVM algorithm is implemented using digital signal processor (DSP). …”
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A comparison of support vector machine and decision tree classifications using satellite data of Langkawi Island by Mohd Shafri, Helmi Zulhaidi, Ramle, F. S. H.

“…The study indicates that the classification accuracy of SVM algorithm was better than DT algorithm. The overall accuracy of the SVM using four kernel types was above 73% and the overall accuracy of the DT method was 69%. …”
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