Search Results - (( a distribution ((svm algorithm) OR (_ algorithm)) ) OR ( parametric estimation bleu algorithm ))

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.

“…SVM is a classification technique developed by Vapnik [1] but a practical difficulty of using SVM is the selection of parameters such as C and kernel parameter, � in Gaussian RBF kernel. …”

Parallel execution of distributed SVM using MPI (CoDLib) by Salleh N.S.M., Suliman A., Ahmad A.R.

“…To reduce the computational time during the process of training the SVM, a combination of distributed and parallel computing method, CoDLib have been proposed. …”

Forecasting FTSE Bursa Malaysia KLCI Trend with Hybrid Particle Swarm Optimization and Support Vector Machine Technique by Lee, Zhong Zhen, Choo, Yun Huoy, Draman @ Muda, Azah Kamilah, Abraham, Ajith

“…The SVM algorithm uses the Radial Basis Function (RBF) kernel function and optim ization of the gam ma and large margin parameters are done using the PSO algorithm. …”
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Oil palm mapping over Peninsular Malaysia using Google Earth Engine and machine learning algorithms by Shaharum, Nur Shafira Nisa, Mohd Shafri, Helmi Zulhaidi, Wan Ab. Karim Ghani, Wan Azlina, Samsatli, Sheila, Al-Habshi, Mohammed Mustafa, Yusuf, Badronnisa

“…However, RF extracted oil palm information better than the SVM. The algorithms were compared and the McNemar's test showed significant values for comparisons between SVM and CART and RF and CART. …”
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A new classifier based on combination of genetic programming and support vector machine in solving imbalanced classification problem by Mohd Pozi, Muhammad Syafiq

“…In addition, the classifier is also optimized such that it has a good generalization property. The main keys of the new classifier are based on the new kernel method, new learning metric and a new optimization algorithm in order to optimize the SVM decision function. …”
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Fault classification in smart distribution network using support vector machine by Chuan O.W., Ab Aziz N.F., Yasin Z.M., Salim N.A., Wahab N.A.

“…Fault identification and classification based machine learning application in power industries have gain significant accreditation due to its great capability and performance. In this paper, a machine-learning algorithm known as Support Vector Machine (SVM) for fault type classification in distribution system has been developed. …”

Performance analysis of support vector machine, Gaussian Process Regression, sequential quadratic programming algorithms in modeling hydrogen-rich syngas production from catalyzed... by Ayodele B.V., Mustapa S.I., Kanthasamy R., Mohammad N., AlTurki A., Babu T.S.

Interaction effect of process parameters and Pd-electrocatalyst in formic acid electro-oxidation for fuel cell applications: Implementing supervised machine learning algorithms by Hossain S.K.S., Ali S.S., Rushd S., Ayodele B.V., Cheng C.K.

A comparative analysis of LSTM, SVM, and GSTANN models for enhancing solar power prediction by M. Helmy, Muhammad Fareezy Fahmy, Yusoff, Siti Hajar, Mansor, Hasmah, Gunawan, Teddy Surya, Chowdhury, Israth Jahan, Mohd Sapihie, Siti Nadiah

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Prediction of hydropower generation via machine learning algorithms at three Gorges Dam, China by Sattar Hanoon M., Najah Ahmed A., Razzaq A., Oudah A.Y., Alkhayyat A., Feng Huang Y., kumar P., El-Shafie A.

“…Therefore, this study investigates the capability of various machine learning algorithms in predicting the power production of a reservoir located in China using data from 1979 to 2016. …”

Classification of imbalanced travel mode choice to work data using adjustable svm model by Qian, Y., Aghaabbasi, M., Ali, M., Alqurashi, M., Salah, B., Zainol, R., Moeinaddini, M., Hussein, E.E.

“…This study deals with imbalanced mode choice data by developing an algorithm (SVMAK) based on a support vector machine model and the theory of adjusting kernel scaling. …”
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Comparative analysis on the deployment of machine learning algorithms in the distributed brillouin optical time domain analysis (BOTDA) fiber sensor by Nordin N.D., Zan M.S.D., Abdullah F.

Performance Evaluation Of Space Vector Modulation (SVM) For Multilevel Inverters by Sanusi, Syamim

“…In such way, the computational burden can be minimized as the SVM tasks are distributed into two parts, in which every part is executed by a single controller. …”
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Predicting Customer Buying Decisions for Online Shopping with Unbalanced Data Set by Yap, Chau Tean

“…The algorithms involved were K-Nearest Neighbor (KNN), Naïve Bayers, J48, Support Vector Machine (SVM), Sequential Minimal Optimization (SMO) and Multilayer Perceptron (MLP). …”
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Performance improvement through optimal location and sizing of distributed generation / Zuhaila Mat Yasin by Mat Yasin, Zuhaila

“…Later, a Least-Squares Support Vector Machine (LS-SVM) model was developed using cross-validation technique. …”
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Cross-project software defect prediction by Bala, Yahaya Zakariyau, Abdul Samat, Pathiah, Sharif, Khaironi Yatim, Manshor, Noridayu

“…In this work, five research questions covering the classification algorithms, dataset, independent variables, performance evaluation metrics used in CPDP studies, and as well as the performance of individual machine learning classification algorithms in predicting software defects across different software projects were addressed accordingly. …”
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A stylometry approach for blind linguistic steganalysis model against translation-based steganography by Mohd Lokman, Syiham

“…While targeted steganalysis is designed to attack a specific embedding algorithm, blind steganalysis use features extracted or selection from the medium to detect any anomalies that indicate a possibility that a secret data has been embedded within the medium. …”
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Application of Machine Learning Technique Using Support Vector Machine in Wind Turbine Fault Diagnosis by Binti Shahrulhisham N.N.H., Chong K.H., Yaw C.T., Koh S.P.

Optimized techniques for landslide detection and characteristics using LiDAR data by Mezaal, Mustafa Ridha

“…The overall accuracy of the Support Vector Machine SVM and Random Forest RF classifiers revealed that three of the six algorithms exhibited higher ranks in the landslide detection. …”
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Classification of transient disturbance using Wavelet based support vector machine / Fahteem Hamamy Anuwar by Anuwar, Fahteem Hamamy

“…In this research, Multilayer perception (MLP) of feedforward Artificial Neural Network (ANN) has also been used as the classifier and comparison are made between the SVM and ANN method. 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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