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1
Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…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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2
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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Article -
3
Classification of basal stem rot disease in oil palm using dielectric spectroscopy
Published 2018“…First, features selection algorithms (genetic algorithm (GA), random forest (RF), and support vector machine-feature selection (SVM-FS)) were used to select the most significant frequencies. …”
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4
Comparison of Logistic Regression, Random Forest, SVM, KNN Algorithm for Water Quality Classification Based on Contaminant Parameters
Published 2024“…This research provides new insights into the application of machine learning algorithms for water quality management as well as guidance for optimal algorithm selection.…”
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5
Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection
Published 2022“…The simulation is implemented with iFogSim and java programming language. …”
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6
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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7
An Arabic hadith text classification model using convolutional neural network and support vector machine / Mohd Irwan Mazlin
Published 2022“…Second, parameter tuning is conducted to find the best parameter for CNN-SVM. Third, the model (CNN-SVM, CNN and SVM) is monitored to see if their performance predicts unseen data. …”
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8
Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing
Published 2011“…Global pheromone update is performed after the completion of processing the jobs in order to reduce the pheromone value of resources. A simulation environment was developed using Java programming to test the performance of the proposed EACO algorithm against existing grid resource management algorithms such as Antz algorithm, Particle Swarm Optimization algorithm, Space Shared algorithm and Time Shared algorithm, in terms of processing time and resource utilization. …”
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9
Ant colony optimization algorithm for load balancing in grid computing
Published 2012“…The proposed algorithm is known as the enhance ant colony optimization (EACO). …”
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Monograph -
10
Classification Of Cervical Cancer Stage From Pap Smear Tests
Published 2019“…The proposed approach will implement stages of image pre-processing, feature selection and extraction as well as classification of classes. …”
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Final Year Project -
11
Improvement of land cover mapping using Sentinel 2 and Landsat 8 imageries via non-parametric classification
Published 2020“…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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12
Development of colorization of grayscale images using CNN-SVM
Published 2021“…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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Book Chapter -
13
OPTIMIZED MIN-MIN TASK SCHEDULING ALGORITHM FOR SCIENTIFIC WORKFLOWS IN A CLOUD ENVIRONMENT
Published 2023“…To achieve this, we propose a new noble mechanism called Optimized Min-Min (OMin-Min) algorithm, inspired by the Min-Min algorithm. …”
Review -
14
Mixed waste classification based on vision inspection / Hassan Mehmood Khan
Published 2022“…Four classification algorithms specifically the Cubic SVM (C.SVM), Quadratic SVM (Q.SVM), Ensemble Bagged Trees (EBT) and k-Nearest Neighbor (kNN) are employed to test the classification accuracy. …”
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15
Pathway-based analysis with Support Vector Machine (SVM-LASSO) for gene selection and classification
Published 2017“…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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16
Talent classification using support vector machine technique / Hamidah Jantan, Norazmah Mat Yusof and Mohd Hanapi Abdul Latif
Published 2014“…Support Vector Machine (SVM) is among the popular learning algorithm for classification in soft computing techniques. …”
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Research Reports -
17
Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization
Published 2019“…This study proposes a car parking management system which applies Dijkstra’s algorithm, Ant Colony Optimization (ACO) and Binary Search Tree (BST) in structuring a guidance system for indoor parking. …”
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18
Pathway-based analysis with support vector machine (SVM-LASSO) for gene selection and classification
Published 2017“…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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Article -
19
The comparative study of model-based and appearance based gait recognition for leave bag behind
Published 2018“…In this research, the analysis performed using two methods which are Model-Based approaches and Appearance-Based approaches. The selected methods were implemented in MATLAB R2014a and R Studio and tested with a standard dataset from the Chinese Academy of Science (CASIA) and tested using two classifiers which is Support Vector Machine (SVM) and KNN (K nearest Neighbour) based on accuracy and misclassification rates (MER) metrics. …”
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Thesis -
20
A stylometry approach for blind linguistic steganalysis model against translation-based steganography
Published 2023“…The proposed stylometry-based blind steganalysis model consists of two stages, which are stylometric feature selection and classification. 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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