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1
A comparison of support vector machine and decision tree classifications using satellite data of Langkawi Island
Published 2009“…The classification using SVM method was implemented automatically by using four kernel types; linear, polynomial, radial basis function and sigmoid. …”
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2
Agarwood oil quality classification using one versus all strategies in multiclass on SVM model / Aqib Fawwaz Mohd Amidon … [et al.]
Published 2021“…Support vector machine (SVM) has been chosen as a main model and for the specific function algorithm was multiclass function. …”
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3
Improvement of land cover mapping using Sentinel 2 and Landsat 8 imageries via non-parametric classification
Published 2020“…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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4
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
Published 2021“…The cubic kernel function was found suitable for training SVMs. Besides, a feed-forward artificial neural network with the backpropagation algorithm and a polynomial surface fit model have also been developed to predict the MIT. …”
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A study on component-based technology for development of complex bioinformatics software
Published 2004“…The second layer uses discriminative SVM algorithm with a state-of-the-art string kernel based on PSI-BLAST profiles that is used to leverage the unlabeled data. …”
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6
SVM-based geospatial prediction of soil erosion under static and dynamic conditioning factors
Published 2018“…Using area under the curve (AUC) and Cohen’s kappa index (k) as the validation criteria, the results showed that polynomial function had the highest performance followed by linear and radial basis function. …”
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7
Performance improvement through optimal location and sizing of distributed generation / Zuhaila Mat Yasin
Published 2014“…To enhance the robustness of the algorithm, the QIEP technique is constructed based on multiobjective model in which the multiobjective functions consist of reducing power losses, increasing maximum loadability and cost minimisation. …”
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8
Implementation of machine learning algorithms for streamflow prediction of Dokan dam
Published 2023“…This study aims at comparing the application of deep learning algorithms and conventional machine learning algorithms for predicting reservoir inflow. …”
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9
A new technique for maximum load margin estimation and prediction
Published 2023“…A new developed index, Voltage Stability Condition Indicator (VSCI) was used as the fitness function for FAIS and FAISVM in order to evaluate the stability condition of load bus in the system. …”
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A preliminary study on automated freshwater algae recognition and classification system / Hayat Mansoor Abdullah
Published 2012“…Then, Image segmentation applied by using canny edge detection algorithm with specific morphological operation to isolate the image objects components. …”
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11
Correlation Feature Selection Weighting Algorithms for Better Support Vector Classification: An Empirical Study
Published 2020“…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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Terahertz sensing analysis for early detection of ganoderma boninense disease using near infrared (NIR) spectrometer
Published 2023“…In classification, four different ML algorithms: K-Nearest Neighbour (kNN), Naïve Bayes (NB), Support Vector Machine (SVM) and Decision Tree (DT) are tested to classify healthy and infected oil palm samples. …”
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13
Implementation of Space Vector Modulation for Voltage Source Inverter
Published 2013“…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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14
Comparison of Logistic Regression, Random Forest, SVM, KNN Algorithm for Water Quality Classification Based on Contaminant Parameters
Published 2024“…This study compares four machine learning algorithms Logistic Regression, Random Forest, Support Vector Machine (SVM), and K-Nearest Neighbors (KNN) in water quality classification based on contaminant parameters. …”
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15
SVM based hysteresis current controller for a three phase active power filter
Published 2004“…The switching control algorithms of the proposed SVM based HCC manage to generate compensated current according to the reference current harmonics extraction is based on the instantaneous active and reactive power theorem in time domain by calculating the power compensation. …”
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16
Support Vector Machines (SVM) in Test Extraction
Published 2006“…This project's objective is to create a summarizer, or extractor, based on machine learning algorithms, which are namely SVM and K-Means. …”
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Support Vector Machines (SVM) in Test Extraction
Published 2006“…This project's objective is to create a summarizer, or extractor, based on machine learning algorithms, which are namely SVM and K-Means. …”
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Final Year Project -
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SVM based hysteresis current controller for a three phase active power filter
Published 2004“…The proposed SVM based HCC is implemented in a closed loop control system. …”
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Prediction of COVID-19 outbreak using Support Vector Machine / Muhammad Qayyum Mohd Azman
Published 2024“…In response to the unprecedented challenges posed by the COVID-19 pandemic, this research project presents a systematic approach to outbreak prediction, specifically advocating for the implementation of Support Vector Machine (SVM) algorithms. …”
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20
Thematic textual hadith classification: an experiment in rapidminer using support vector machine (SVM) and naïve bayes algorithm
Published 2020“…From the results, the different value of accuracy for both SVM and Naïve Bayes Algorithm was 2.4%. The Naïve Bayes Algorithm displayed better result comparing to SVM. …”
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