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Correlation Feature Selection Weighting Algorithms for Better Support Vector Classification: An Empirical Study by Sim, Doreen Ying Ying, Teh, Chee Siong, Ahmad Izuanuddin, Ismail

“…Proposed cfsw-SVM algorithms are then developed. Proposed formulations on SVM regularization parameter provides synergistic adjustments between prediction or classification accuracy and the level of correlations among features in the SVM implemented. …”
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SVM based hysteresis current controller for a three phase active power filter by Leow, Pei Ling, Ahmad Azli, Naziha

“…A space vector modulation (SVM) based hysteresis current controller (HCC) technique for a three phase shunt active power filter is proposed. …”
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SVM based hysteresis current controller for a three phase active power filter by Leow, Pei Ling

“…The proposed SVM based HCC is implemented in a closed loop control system. …”
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Financial time series predicting using machine learning algorithms by Tiong, Leslie Ching Ow *

“…Thereafter, Artificial Neural Network (ANN) and Support Vector Machine (SVM) algorithms are implemented separately to train with the trend patterns for predicting the movement direction of financial trends. …”
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Optimizing in-car-abandoned children’s sounds detection using deep learning algorithms / Nur Atiqah Izzati Md Fisol by Md Fisol, Nur Atiqah Izzati

“…The results demonstrate the effectiveness of the proposed deep neural network, achieving an impressive classification accuracy of 99%, outperforming the SVM model which achieved an accuracy of 98%. …”
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Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

“…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
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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. Overall, SVM algorithm performed better than k-NN in terms of classification accuracy, achieving a value of 97.10% compared to k-NN’s 70.60%. …”
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Development of colorization of grayscale images using CNN-SVM by Abualola, Abdallah, Gunawan, Teddy Surya, Kartiwi, Mira, Ambikairajah, Eliathamby, Habaebi, Mohamed Hadi

“…Support Vector Machine (SVM) regression was used at the final stage. The proposed algorithm was implemented using Python with Keras and Tensorflow libraries in Google Colab. …”
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An Arabic hadith text classification model using convolutional neural network and support vector machine / Mohd Irwan Mazlin by Mazlin, Mohd Irwan

“…First, different model performances are being analysed to find which model gives higher accuracy for this study. CNN-SVM shows a promising result with 92% accuracy, while the CNN only and SVM only give lower accuracy than the proposed model with 82% and 74%. …”
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Effects of Different Pre-Trained Deep Learning Algorithms as Feature Extractor in Tomato Plant Health Classification by Chong, Hou Ming, Yin Yap, Xien, Seng Chia, Kim

“…A Raspberry Pi coupled with a camera was proposed to capture tomato plant leaf image. After that, a support vector machine (SVM) with the extracted features was trained for the plant health classification. …”
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Implementation of welch pre-processing in SVM algorithm for improved accuracy on EEG data by Hariyady Hariyady, Ag Asri Ag Ibrahim, Jason Teo, Muhammad Balya Firjaun Barlaman, Muhammad Aulanas Bitaqwa, Azhana Ahmad, Fouziah Md Yassin, Carolyn Salimun, Ng, Giap Weng

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SVM driven approach for detecting DoS attacks in SDN environment by Najmun, Nisa, Adnan Shahid, Khan, Azman, Bujang Masli, Nusrat, Shaheen

“…To address this challenge, we propose a novel approach that efficiently detects DoS attacks by implementing a packet inspection process using a queuing mechanism, followed by machine learning classification using SVM and KNN algorithms. …”
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Lightning Fault Classification for Transmission Line Using Support Vector Machine by Asman S.H., Aziz N.F.A., Kadir M.Z.A.A., Amirulddin U.A.U., Roslan N., Elsanabary A.

“…The classification performance of the developed algorithms was evaluated using confusion matrix. Overall, SVM algorithm performed better than k-NN in terms of classification accuracy, achieving a value of 97.10% compared to k-NN's 70.60%. …”

Classification Of Cervical Cancer Stage From Pap Smear Tests by Sendal, Ken Irok

“…Then, classification methods for the classification of classes in these cells such as K-Nearest Neighborhood (KNN) and Support Vector Machine (SVM) were explored. The performance of the proposed classification algorithm gave satisfactory results of accuracy, 91.9% for KNN classification and 95.0% for SVM classification.…”
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Effects of Different Pre-Trained Deep Learning Algorithms as Feature Extractor in Tomato Plant Health Classification by Hou Ming Chong, Hou Ming Chong, Xien Yin Yap, Xien Yin Yap, Kim Seng Chia, Kim Seng Chia

“…A Raspberry Pi coupled with a camera was proposed to capture tomato plant leaf image. After that, a support vector machine (SVM) with the extracted features was trained for the plant health classification. …”
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Effects of Different Pre-Trained Deep Learning Algorithms as Feature Extractor in Tomato Plant Health Classification by Hou Ming Chong, Hou Ming Chong, Xien Yin Yap, Xien Yin Yap, Kim Seng Chia, Kim Seng Chia

“…A Raspberry Pi coupled with a camera was proposed to capture tomato plant leaf image. After that, a support vector machine (SVM) with the extracted features was trained for the plant health classification. …”
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Effects of Different Pre-Trained Deep Learning Algorithms as Feature Extractor in Tomato Plant Health Classification by Hou Ming Chong, Hou Ming Chong, Xien Yin Yap, Xien Yin Yap, Kim Seng Chia, Kim Seng Chia

“…A Raspberry Pi coupled with a camera was proposed to capture tomato plant leaf image. After that, a support vector machine (SVM) with the extracted features was trained for the plant health classification. …”
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Smart fall detection by enhanced SVM with fuzzy logic membership function by Harum, Norharyati, Khalil, Mohamad Kchouri, Hazimeh, Hussein, Obeid, Ali

“…Because combining these two algorithms is not an easy task, we leverage SVM with a kernel comprised of a fuzzy membership function and thus build a new model known as FSVM. …”
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Automatic Segmentation and Classification of Skin Lesions in Dermoscopic Images by Adil Humayun, Khan

“…This proposed algorithm achieved segmentation accuracy of 96.8% and 92.1% for ISIC and PH2 datasets respectively. …”
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Talent classification using support vector machine technique / Hamidah Jantan, Norazmah Mat Yusof and Mohd Hanapi Abdul Latif by Jantan, Hamidah, Mat Yusof, Norazmah, Abdul Latif, Mohd Hanapi

“…Support Vector Machine (SVM) is among the popular learning algorithm for classification in soft computing techniques. …”
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