Improved Salp Swarm Algorithm based on opposition based learning and novel local search algorithm for feature selection

Research article (Expert Systems with Applications, 2019) · cited 377× · AI/ML
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Improved Salp Swarm Algorithm based on opposition based learning and novel local search algorithm for feature selection

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Improved Salp Swarm Algorithm based on opposition based learning and novel local search algorithm for feature selection is a scholarly article[1].

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APA 4ort.xyz Knowledge Graph. (2026). Improved Salp Swarm Algorithm based on opposition based learning and novel local search algorithm for feature selection. Retrieved May 24, 2026, from https://4ort.xyz/entity/improved-salp-swarm-algorithm-based-on-opposition-based-learning-and-novel-local-search-algorithm-for-feature-selection
MLA “Improved Salp Swarm Algorithm based on opposition based learning and novel local search algorithm for feature selection.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/improved-salp-swarm-algorithm-based-on-opposition-based-learning-and-novel-local-search-algorithm-for-feature-selection.
BibTeX @misc{4ortxyz_improved-salp-swarm-algorithm-based-on-opposition-based-learning-and-novel-local-search-algorithm-for-feature-selection_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Improved Salp Swarm Algorithm based on opposition based learning and novel local search algorithm for feature selection}}, year = {2026}, url = {https://4ort.xyz/entity/improved-salp-swarm-algorithm-based-on-opposition-based-learning-and-novel-local-search-algorithm-for-feature-selection}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Improved Salp Swarm Algorithm based on opposition based learning and novel local search algorithm for feature selection — https://4ort.xyz/entity/improved-salp-swarm-algorithm-based-on-opposition-based-learning-and-novel-local-search-algorithm-for-feature-selection (retrieved 2026-05-24)

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