A new binary grasshopper optimization algorithm for feature selection problem
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TL;DR: In this paper , a new binary variant of the grasshopper optimization algorithm is proposed and used for the feature subset selection problem, which is tested and compared to five well-known swarm-based algorithms used in feature selection problem.
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About: This article is published in Journal of King Saud University - Computer and Information Sciences. The article was published on 01 Feb 2022. and is currently open access. The article focuses on the topics: Feature selection & Binary number.
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Citations
Metaheuristic Algorithms on Feature Selection: A Survey of One Decade of Research (2009-2019)
TL;DR: In this article, an extensive literature review on solving feature selection problem using metaheuristic algorithms which are developed in the ten years (2009-2019) is presented, and a categorical list of more than a hundred metaheuristics algorithms is presented.
Grasshopper Optimization Algorithm: Theory, Variants, and Applications
TL;DR: A comprehensive review of GOA based on more than 120 scientific articles published by leading publishers: IEEE, Springer, Elsevier, IET, Hindawi, and others is presented in this article.
A novel binary gaining–sharing knowledge-based optimization algorithm for feature selection
TL;DR: This study checks the performance of recently developed gaining–sharing knowledge-based optimization algorithm (GSK), and proposes a novel binary version of GSK algorithm that relies on these two stages with knowledge factor 1 and FS-pBGSK: a population reduction technique that is employed on BGSK algorithm to enhance the exploration and exploitation quality of FS-B GSK.
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Virtual Collection for Distributed Photovoltaic Data: Challenges, Methodologies, and Applications
TL;DR: In this paper , a comprehensive and systematic review of virtual collection of distributed photovoltaic systems (DPVS) is provided, including the main methods applicable to virtual collection, including similarity analysis, reference station selection, and PV data inference.
Boolean Particle Swarm Optimization with various Evolutionary Population Dynamics approaches for feature selection problems
TL;DR: In this article , a feature selection approach based on a Boolean variant of Particle Swarm Optimization (BPSO) boosted with Evolutionary Population Dynamics (EPD) is proposed.
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