Search Results - (( java implication based algorithm ) OR ( through implementation svm algorithm ))

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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Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde by Ogunfolajin Maruff , Tunde

“…The support vector machines (SVM) algorithm obtained the overall best results of 94.5% accuracy, 91.8% precision, 91.7% recall, and 91.1% f-Measure while the naïve bayes (NB) algorithm obtained the best AUC score of 0.944 with the tweet data of Dato Seri Anwar. …”
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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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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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SVM-based geospatial prediction of soil erosion under static and dynamic conditioning factors by Muhammad Raza, Ul Mustafa, Abdulkadir, Taofeeq Sholagber, Khamaruzaman, Wan Yusof, Ahmad Mustafa, Hashim, M., Waris, Muhammad, Shahbaz

“…The study implements four kernel tricks of SVM with sequential minimal optimization algorithm as a classifier for soil erosion susceptibility modeling. …”
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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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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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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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Performance improvement through optimal location and sizing of distributed generation / Zuhaila Mat Yasin by Mat Yasin, Zuhaila

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Automatic Segmentation and Classification of Skin Lesions in Dermoscopic Images by Adil Humayun, Khan

“…In the third classification algorithm, hybrid features are extracted using AlexNet and VGG-16 through a transfer learning approach where parameter manipulation is implemented to simplify the network. …”
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P300 detection of brain signals using a combination of wavelet transform techniques by Motlagh, Farid Esmaeili

“…In this research the BCI competition data-set has been processed through 5 optimized detection methods. Wavelet transform (WT), student’s two-sample t-statistic (T-Test) and support vector machines (SVM) used in designing the algorithms. …”
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Real-time human activity recognition using external and internal spatial features by Htike@Muhammad Yusof, Zaw Zaw, Egerton, Simon, Kuang, Ye Chow

“…Activities are classified by a support vector machine (SVM) with a radial basis kernel. Optimal parameters for the SVM are found through a 10-fold cross-validation. …”
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Sentiment analysis of customer review for Tina Arena Beauty by Amri, Nur Najwa Shahirah

“…Three machine learning algorithms Naive Bayes, Random Forest, and Support Vector Machine (SVM) were evaluated, and SVM achieved the highest accuracy and was selected as the final classifier. …”
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Malay festive seasons food recognition for calorie detection using SVM and ECOC approaches / Nurul Hafiza Binti Basiruddin, Zalikha Zulkifli and Samsiah Ahmad by Basiruddin, Nurul Hafiza, Zulkifli, Zalikha, Ahmad, Samsiah

“…Then the result from the Color Feature Extraction Method is used to identify the type of food by using Error-Correcting Output Codes (ECOC) classification, which is part of the Support Vector Machine (SVM) algorithm. The reliability and effectiveness of the classifier are evaluated through system testing, where the total overall percentage of correct recognition performed by the system is 82.5%, according to the correct and wrong recognition obtained. …”
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Comparative Analysis of Cervical Cell Classification Using Machine Learning Algorithms by Wan Azani Mustafa, Khalis Khiruddin, Khairur Rijal Jamaludin, Firdaus Yuslan Khusairi, Shahrina Ismail

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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Hospital site suitability assessment using three machine learning approaches: evidence from the Gaza strip in Palestine by Almansi, Khaled Yousef, Mohamed Shariff, Abdul Rashid, Abdullah, Ahmad Fikri, Syed Ismail, Sharifah Norkhadijah

“…The CFS analysis shows very high correlations with R2 values of 0.94, 0. 93, and 0.75 for the SVM, MLP, and LR models, respectively. Moreover, based on areas under the ROC curve, the MLP model produced a prediction accuracy of 84.90%, SVM of 75.60%, and LR of 64.40%. …”
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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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Data mining for structural damage identification using hybrid artificial neural network based algorithm for beam and slab girder / Meisam Gordan by Meisam , Gordan

“…In the modeling phase, amongst all DM algorithms, the applicability of machine learning, artificial intelligence and statistical data mining techniques were examined using Support Vector Machine (SVM), Artificial Neural Network (ANN) and Classification and Regression Tree (CART) to detect the hidden patterns in vibration data. …”
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Design of Predictive Model for TCM Tongue Diagnosis In Malaysia Using Machine Learning by Koe, Jia Chi

“…Six supervised machine learning algorithms (Linear Regression, Logistic Regression, K Nearest Neighbors (KNN), Decision Trees (DT), Support Vector Machine (SVM) and Random Forest) are used to perform disease prediction. …”
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