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code encryption » secure encryption (Expand Search)
code selection » gene selection (Expand Search)
wide selection » wheel selection (Expand Search), gene selection (Expand Search)
code encryption » secure encryption (Expand Search)
code selection » gene selection (Expand Search)
wide selection » wheel selection (Expand Search), gene selection (Expand Search)
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UniBFS: A novel uniform-solution-driven binary feature selection algorithm for high-dimensional data
Published 2024“…To overcome these challenges, a new FS algorithm named Uniform-solution-driven Binary Feature Selection (UniBFS) has been developed in this study. …”
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Gene selection for microarray data classification based on Gray Wolf Optimizer enhanced with TRIZ-inspired operators
Published 2021“…Pattern recognition algorithms are widely applied to gene expression data to differentiate between health and cancerous patient samples. …”
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Multi-marker-LD based genetic algorithm for tag SNP selection
Published 2014“…The performance of the three algorithms are compared with those of a recognized tag SNP selection algorithm using three different real data sets from the HapMap project. …”
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Intelligent Hybrid Feature Selection for Textual Sentiment Classification
Published 2021“…Effective feature extraction and selection are significant for the SA because they can boost the learning algorithm’s predictive performance while reducing the high-dimensional feature space. …”
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Minimum traffic inter-BS SHO boundary selection algorithm for CDMA-based wireless networks
Published 2004“…An algorithm is presented to select an inter-base station soft handoff (inter-BS SHO) boundary for code division multiple access (CDMA)-based wireless networks. …”
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Large language models for code completion: A systematic literature review
Published 2024“…Different techniques can achieve code completion, and recent research has focused on Deep Learning methods, particularly Large Language Models (LLMs) utilizing Transformer algorithms. …”
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Simultaneous stabilization of multimachine power systems viagenetic algorithms
Published 1999“…This paper demonstrates the use of genetic algorithms for the simultaneous stabilization of multimachine power systems over a wide range of operating conditions via single-setting power system stabilizers. …”
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Genetic Algorithm Based Simultaneous Eigenvalue Placement Of Power Systems
Published 2020“…This paper demonstrates the use of genetic algorithms to design a single output feedback control law for the simultaneous eigenvalue placement of a power system running over a wide range of operating conditions. …”
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Eye-Clustering: An Enhanced Centroids Prediction for K-means Algorithm
Published 2024“…This work aims to enhance the performance of the K-means algorithm by introducing a novel method for selecting the initial centroids, thereby minimizing randomness and reducing the number of iterations needed to reach optimal results. …”
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Assessment and Performance Analysis of Machine Learning Techniques for Gas Sensing E-nose Systems
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NOVEL STACKING CLASSIFICATION AND PREDICTION ALGORITHM BASED AMBIENT ASSISTED LIVING FOR ELDERLY
Published 2022“…Therefore, this thesis proposed a Novel Stacking Classification and Prediction (NSCP) algorithm based on AAL for the older people with Multi-strategy Combination based Feature Selection (MCFS) and Novel Clustering Aggregation (NCA) algorithms. …”
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Optimal multiobjective design of robust power system stabilizers using genetic algorithms
Published 2003“…The problem of robustly selecting the parameters of the power system stabilizers is converted to an optimization problem which is solved by a genetic algorithm with the eigenvalue-based multiobjective function. …”
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Prediction of pressure gradient for oil-water flow: A comprehensive analysis on the performance of machine learning algorithms
Published 2022“…This study aims to develop five robust machine learning (ML) algorithms and their fusions for a wide range of flow patterns (FP) regimes. …”
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A Hybrid Intrusion Detection Model Using EGA-PSO and Improved Random Forest Method
Published 2022“…Machine learning (ML) methods are widely used in IDS. Due to a limited training dataset, an ML-based IDS generates a higher false detection ratio and encounters data imbalance issues. …”
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COMPUTER AIDED PROGRAMMING EDUCATION (CAPE)
Published 2020“…CAPE consists of problem definition and algorithm construction modules. Algorithm construction module is currently supported with a facility to map an algorithm(s) into FORTRAN or Pascal code. …”
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