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SVM, ANN, and PSF modelling approaches for prediction of iron dust minimum ignition temperature (MIT) based on the synergistic effect of dispersion pressure and concentration by Arshad, U., Taqvi, S.A.A., Buang, A., Awad, A.

“…The data has been divided into 'Training Set' and 'Testing Set'. The implementation and efficacy of machine learning and statistical approaches have been demonstrated through real-time experimental results. …”
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Improvement of land cover mapping using Sentinel 2 and Landsat 8 imageries via non-parametric classification by Myaser, Jwan

“…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 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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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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The formulation of a transfer learning pipeline for the classification of the wafer defects by Lim, Shi Xuen

“…Thus, this study will aim to explore 17 types of TL models, and classify the features extracted using 3 different ML algorithms, namely Support Vector Machine (SVM), k-Nearest Neighbor (kNN) and Random Forest (RF). …”
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Implementation of advanced techniques in production and manufacturing sectors through support vector machine algorithm with embedded system by Rayner Alfred, Narender Chinthamu, T. Jayanthy, Elangovan Muniyandy, Tarun Kumar Dhiman, Nimmy John T.

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Automatic Classification of Cervix Type by Muktiar Singh, Jasdeep Singh

“…In this experiment, the SVM method of classification was used to obtain an accuracy of 76.2%.…”
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Pathway-based analysis with Support Vector Machine (SVM-LASSO) for gene selection and classification by Nasrudin, Nurul Athirah, Chan, Weng Howe, Mohamad, Mohd Saberi, Deris, Safaai, Napis, Suhaimi, Kasim, Shahreen

“…Secondly, Support Vector Machine with Least Absolute Shrinkage and Selection Operator algorithm (SVM-LASSO) is proposed, which to find informative genes for each pathway to ensure efficient gene selection and classification in every pathway. …”
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Classification of transient disturbance using Wavelet based support vector machine / Fahteem Hamamy Anuwar by Anuwar, Fahteem Hamamy

“…The SVM results show that RBF kernel is superior to linear kernel in classifying the transient with average percentage of 83% This research has also proved that SVM has higher performance than the backpropagation algorithm of the ANN.…”
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Author identification for under-resourced language Kadazandusun by Nursyahirah, Tarmizi, Suhaila, Saee, Dayang Hanani, Abang Ibrahim

“…Besides, this paper also examines the performance of two machine learning algorithms on the KadazanDusun data set by analyzing the stylometric features. …”
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Hybrid ANN and Artificial Cooperative Search Algorithm to Forecast Short-Term Electricity Price in De-Regulated Electricity Market by Pourdaryaei, Alireza, Mokhlis, Hazlie, Illias, Hazlee Azil, Kaboli, S. Hr. Aghay, Ahmad, Shameem, Ang, Swee Peng

“…Finally, the simulation results validated the premise of the proposed hybrid method through enhanced accuracy compared to the results acquired by implementing hybrid support vector machine (SVM) and hybrid ANN optimization methods. © 2013 IEEE.…”
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P300 detection of brain signals using a combination of wavelet transform techniques by Motlagh, Farid Esmaeili

“…Wavelet transform (WT), student’s two-sample t-statistic (T-Test) and support vector machines (SVM) used in designing the algorithms. By using three level of channel reduction, three subgroups of channels with the number of 17, 9, and 5 have been chosen based on their ability in P300 pattern recognition. …”
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A stylometry approach for blind linguistic steganalysis model against translation-based steganography by Mohd Lokman, Syiham

“…The proposed stylometric features selected from a set of cover text are categorized into two group features; lexical and syntactic features before implemented into the model Support Vector Machine (SVM) as the classifier. …”
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Pathway-based analysis with support vector machine (SVM-LASSO) for gene selection and classification by Nurul Athirah, Nasrudin, Chan, Weng Howe, Mohd Saberi, Mohamad, Safaai, Deris, Suhaimi, Napis, Shahreen, Kasim

“…Secondly, Support Vector Machine with Least Absolute Shrinkage and Selection Operator algorithm (SVM-LASSO) is proposed, which to find informative genes for each pathway to ensure efficient gene selection and classification in every pathway. …”
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Camera Independent Face Recognition Algorithm In Visual Surveillance by Yew, Chuu Tian

“…The combination of Linear Discriminant Analysis (LDA) and HE preprocessed images managed to achieve an average recognition rate of 81.48% for the single camera training set. The flandmark facial landmark detector is implemented to determine the location of the eyes and new face images are obtained by cropping the HE pre-processed images. …”
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Ozone Concentration Forecasting Based on Artificial Intelligence Techniques: A Systematic Review by Yafouz A., Ahmed A.N., Zaini N., El-Shafie A.

Novel vector control method for three-stage hybrid cascaded multilevel inverter by Mekhilef, Saad, Kadir, M.N.A.

“…The inverter has been constructed, and the control algorithm has been implemented. Test results show that the proposed algorithm achieves the claimed features, and all major hypotheses have been verified.…”
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The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

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EEG Eye State Identification based on Statistical Feature and Common Spatial Pattern Filter by Woon, W.C., Yahya, N., Badruddin, N.

“…Number of selected electrodes are divided into 3 groups, with 2 groups having a set of 7 different electrodes and 1 group that combined both sets of 7 electrodes giving a total of 14 electrodes. …”
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EEG Eye State Identification based on Statistical Feature and Common Spatial Pattern Filter by Woon, W.C., Yahya, N., Badruddin, N.

“…Number of selected electrodes are divided into 3 groups, with 2 groups having a set of 7 different electrodes and 1 group that combined both sets of 7 electrodes giving a total of 14 electrodes. …”
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