Search Results - (( subset selection mechanism algorithm ) OR ( whale optimization mead algorithm ))*
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Aco-based feature selection algorithm for classification
Published 2022“…However, the MGCACO algorithm has three main drawbacks in producing a features subset because of its clustering method, parameter sensitivity, and the final subset determination. …”
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Improved TLBO-JAYA Algorithm for Subset Feature Selection and Parameter Optimisation in Intrusion Detection System
Published 2020“…ITLBO with supervised machine learning (ML) technique was used for feature subset selection (FSS). The selection of the least number of features without causing an effect on the result accuracy in FSS is a multiobjective optimisation problem. …”
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Rao-SVM machine learning algorithm for intrusion detection system
Published 2020“…Being that feature subset selection is considered a multi-objective optimization problem, this study proposed the Rao-SVM as an FSS mechanism; its algorithm-specific and parameter-less concept was also explored. …”
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Experimental study of variation local search mechanism for bee algorithm feature selection
Published 2017“…The Bees Algorithm (BA) has been applied for finding the best possible subset features of a dataset. …”
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Feature Subset Selection in Intrusion Detection Using Soft Computing Techniques
Published 2011“…Instead of using traditional approach of selecting features with the highest eigenvalues such as PCA, this research applied a Genetic Algorithm (GA) to search the principal feature space that offers a subset of features with optimal sensitivity and the highest discriminatory power. …”
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Feature Subset Selection in Intrusion Detection Using Soft Computing Techniques
Published 2011“…Instead of using traditional approach of selecting features with the highest eigenvalues such as PCA, this research applied a Genetic Algorithm (GA) to search the principal feature space that offers a subset of features with optimal sensitivity and the highest discriminatory power. …”
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Probing mechanism scheduling for connected coverage wireless sensor network.
Published 2011“…Joint scheduling method has considered both requirements by using random scheduling for sensing coverage, which divides sensor nodes to k subsets. Each sensor nodes randomly selects one defined subset. …”
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Performance Evaluation of BPSO & PCA as Feature Reduction Techniques for Bearing Fault Diagnosis
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Conference or Workshop Item -
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Improved intrusion detection algorithm based on TLBO and GA algorithms
Published 2021“…The proposed method combined the New Teaching-Learning-Based Optimization Algorithm (NTLBO), Support Vector Machine (SVM), Extreme Learning Machine (ELM), and Logistic Regression (LR) (feature selection and weighting) NTLBO algorithm with supervised machine learning techniques for Feature Subset Selection (FSS). …”
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Towards a multispectral imaging system for spatial mapping of chemical composition in fresh-cut pineapple (Ananas comosus)
Published 2023“…Ranking and uncorrelatedness (based on ReliefF algorithm) and subset selection (based on CfsSubset algorithm) approaches were applied to find the most informative wavelengths in which bandpass optical filters or light sources are commercially available. …”
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Short Text Classification Using An Enhanced Term Weighting Scheme And Filter-Wrapper Feature Selection
Published 2018“…In the second stage, grey wolf optimization (GWO) algorithm, a new heuristic search algorithm, uses the SVM accuracy as a fitness function to find the optimal subset feature.…”
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Hybrid Artificial Bees Colony algorithms for optimizing carbon nanotubes characteristics
Published 2018“…Optimization is a crucial process to select the best parameters in single and multi-objective problems for manufacturing process.However,it is difficult to find an optimization algorithm that obtain the global optimum for every optimization problem.Artificial Bees Colony (ABC) is a well-known swarm intelligence algorithm in solving optimization problems.It has noticeably shown better performance compared to the state-of-art algorithms.This study proposes a novel hybrid ABC algorithm with β-Hill Climbing (βHC) technique (ABC-βHC) in order to enhance the exploitation and exploration process of the ABC in optimizing carbon nanotubes (CNTs) characteristics.CNTs are widely used in electronic and mechanical products due to its fascinating material with extraordinary mechanical,thermal,physical and electrical properties. …”
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Classification of Immunosignature Using Random Forests for Cancer Diagnosis
Published 2015“…We have used the Random Subset gene selection method to avoid overfitting and improve model performance in order to make the input data suitable for the classification stage, which has been implemented using the Random Forest (RF) classifier. …”
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Proceeding Paper -
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Intrusion Detection in Mobile Ad Hoc Networks Using Transductive Machine Learning Techniques
Published 2011“…Feature selection is undertaken to select the relevant subsets of features to build an efficient prediction model and improve intrusion detection performance by removing irrelevant features. …”
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Hybrid metaheuristics for QOS-aware service composition / Hadi Naghavipour
Published 2022“…Finally, this thesis revealed a parallel hybrid metaheuristic architecture and monitoring mechanism to provide immunity against premature convergence when the composition is performed in a subset of search space as the output of rough set-based heuristics. …”
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