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1
Framework of Meta-Heuristic Variable Length Searching for Feature Selection in High-Dimensional Data
Published 2023“…Meta-heuristic searching with embedding information theory-based criteria in the fitness function for selecting the relevant features is used widely in current feature selection algorithms. …”
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2
Framework of Meta-Heuristic Variable Length Searching for Feature Selection in High-Dimensional Data
Published 2023“…Meta-heuristic searching with embedding information theory-based criteria in the fitness function for selecting the relevant features is used widely in current feature selection algorithms. …”
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3
Framework of Meta-Heuristic Variable Length Searching for Feature Selection in High-Dimensional Data
Published 2023“…Meta-heuristic searching with embedding information theory-based criteria in the fitness function for selecting the relevant features is used widely in current feature selection algorithms. …”
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4
An improved bees algorithm local search mechanism for numerical dataset
Published 2015“…This algorithm performs a kind of exploitative neighbourhoods search combined with random explorative search. …”
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5
An improved electromagnetism-like mechanism algorithm for the optimization of maximum power point tracking / Tan Jian Ding
Published 2017“…The Electromagnetism-Like Mechanism algorithm (EM) is a meta-heuristic algorithm designed to search for global optimum solutions using bounded variables. …”
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6
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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7
An efficient anomaly intrusion detection method with feature selection and evolutionary neural network
Published 2020“…The proposed search algorithm uses mutation to more accurately examine the search space, to allow candidates to escape local minima. …”
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8
A hybrid local search algorithm for minimum dominating set problems
Published 2022“…This algorithm focuses on generating promising solutions in different areas of the solution space using the problem search history. …”
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9
A hybrid local search algorithm for minimum dominating set problems
Published 2022“…This algorithm focuses on generating promising solutions in different areas of the solution space using the problem search history. …”
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10
Ideal combination feature selection model for classification problem based on bio-inspired approach
Published 2020“…The important step is to idealize the combined feature selection models by finding the best combination of search method and feature selection algorithms. …”
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Book Section -
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Metaheuristic algorithms for feature selection (2014–2024)
Published 2025“…Metaheuristic algorithms are suited to provide solutions to feature selection problems because these problems are combinatorial and require an effective and efficient search through large solution spaces. …”
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12
Crow Search Freeman Chain Code (CS-FCC) feature extraction algorithm for handwritten character recognition
Published 2023“…In this research, a Crow Search Algorithm (CSA)-based metaheuristic strategy for feature extraction in HCR was developed. …”
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13
Enhanced grey wolf optimisation algorithm for feature selection in anomaly detection
Published 2022“…The third modification improves the controlled parameter of the MBGWO algorithm using indicators from the search process to refine the solution. …”
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14
Utilizing the roulette wheel based social network search algorithm for substitution box construction and optimization
Published 2023“…This paper introduces a new variant of a recent metaheuristic algorithm based on the Social Network Search algorithm (SNS), which is called the Roulette Wheel Social Network Search algorithm (SNS). …”
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15
Depth linear discrimination-oriented feature selection method based on adaptive sine cosine algorithm for software defect prediction
Published 2024“…DASC-FS integrates the Adaptive Sine Cosine Algorithm (ASCA) as a search algorithm to determine the relevant features and adopts Depth Linear Discriminant Analysis (D-LDA) to identify the discriminative features that maximize class sepa ration. …”
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16
Enhancing Classification Algorithms with Metaheuristic Technique
Published 2024“…Meta-heuristic algorithms are search techniques used to solve complexoptimization problems, and these algorithms can help provide reasonable solutions in a shorter time thanexact methods. …”
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17
Hybrid genetic algorithm with multi-parents recombination for job shop scheduling problems / Ong Chung Sin
Published 2013“…This mechanism is restricted to search the possible solutions in a critical path. …”
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18
Hybrid binary grey Wolf with Harris hawks optimizer for feature selection
Published 2021“…The proposed hybrid method outperforms the BGWO algorithm in terms of accuracy, selected feature size, and computational time. …”
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Hybrid Binary Grey Wolf with Harris Hawks Optimizer for Feature Selection
Published 2021“…The proposed hybrid method outperforms the BGWO algorithm in terms of accuracy, selected feature size, and computational time. …”
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20
Hybrid binary grey Wolf with Harris hawks optimizer for feature selection
Published 2021“…The proposed hybrid method outperforms the BGWO algorithm in terms of accuracy, selected feature size, and computational time. …”
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