Results 11 to 20 of about 10,782 (162)
Metaheuristic Algorithms on Feature Selection: A Survey of One Decade of Research (2009-2019)
IEEE Access, 2021 Feature selection is a critical and prominent task in machine learning. To reduce the dimension of the feature set while maintaining the accuracy of the performance is the main aim of the feature selection problem.
Prachi Agrawal +3 more
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AutoMH: Automatically Create Evolutionary Metaheuristic Algorithms Using Reinforcement Learning [PDF]
Entropy, 2022 Machine learning research has been able to solve problems in multiple domains. Machine learning represents an open area of research for solving optimisation problems. The optimisation problems can be solved using a metaheuristic algorithm, which can find
Boris Almonacid
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Flood algorithm: a novel metaheuristic algorithm for optimization problems [PDF]
PeerJ Computer ScienceMetaheuristic algorithms are an important area of research that provides significant advances in solving complex optimization problems within acceptable time periods.
Ramazan Ozkan, Ruya Samli
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Recent Advances in Metaheuristic Algorithms
AlgorithmsThis paper presents a review of recent advancements in metaheuristic algorithms, emphasizing their broad applicability across research domains and the performance improvements achieved through their derived variants.
Tomislav Ivanovski +2 more
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Nature-inspired metaheuristic algorithms: literature review and presenting a novel classification [PDF]
Journal of Applied Research on Industrial Engineering, 2023 Over the past decade, solving complex optimization problems with metaheuristic algorithms has attracted many experts and researchers.There are exact methods and approximate methods to solve optimization problems. Nature has always been a model for humans
Mehdi Khadem +2 more
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How metaheuristic algorithms can help in feature selection for Alzheimer’s diagnosis [PDF]
International Journal of Research in Industrial Engineering, 2023 Feature selection is the process of picking the most effective feature among a considerable number of features in the dataset. However, choosing the best subset that gives a higher performance in classification is challenging.
Farzaneh Salami +2 more
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Metaheuristics: A Review of Algorithms
International Journal of Online and Biomedical Engineering (iJOE), 2023 In science and engineering, many optimization tasks are difficult to solve, and the core concern these days is to apply metaheuristic (MH) algorithms to solve them. Metaheuristics have gained significant attention in recent years, with nature serving as the fundamental inspiration where self-organization property led to collective intelligence emerging
Haval Tariq Sadeeq +1 more
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Survey of Lévy Flight-Based Metaheuristics for Optimization
Mathematics, 2022 Lévy flight is a random walk mechanism which can make large jumps at local locations with a high probability. The probability density distribution of Lévy flight was characterized by sharp peaks, asymmetry, and trailing.
Juan Li +4 more
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An Overview of the Concepts, Classifications, and Methods of Population Initialization in Metaheuristic Algorithms [PDF]
Journal of Advances in Computer Engineering and Technology, 2021 Metaheuristic algorithms are typically population-based random search techniques. The general framework of a metaheuristic algorithm consisting of its main parts.
Mohammad Hassanzadeh, farshid keynia
doaj
Online metaheuristic algorithm selection
Expert Systems with Applications, 2022 The performance of optimization algorithms significantly depends on the landscape of the problems. It is known that there is no single algorithm that outperforms others on problems with different fitness landscapes. One of the issues in metaheuristic algorithms is keeping the balance between exploration and exploitation.
Kazem Meidani +2 more
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