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Reinforcement learning-controlled differential evolution with L-BFGS refinements.

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Title: Reinforcement learning-controlled differential evolution with L-BFGS refinements.
Authors: Cao Y; School of Computer Science and Engineering, Shenyang Jianzhu University, Shenyang, China.; Liaoning Provincial Key Laboratory of Big Data Management and Analysis of Urban Construction, Shenyang, China.; Shenyang Branch of National Special Computer Engineering Technology Research Center, Shenyang, China., Wu B; School of Computer Science and Engineering, Shenyang Jianzhu University, Shenyang, China.; Liaoning Provincial Key Laboratory of Big Data Management and Analysis of Urban Construction, Shenyang, China.; Shenyang Branch of National Special Computer Engineering Technology Research Center, Shenyang, China., Wen M; School of Computer Science and Engineering, Shenyang Jianzhu University, Shenyang, China.; Liaoning Provincial Key Laboratory of Big Data Management and Analysis of Urban Construction, Shenyang, China.; Shenyang Branch of National Special Computer Engineering Technology Research Center, Shenyang, China.
Source: PloS one [PLoS One] 2026 May 13; Vol. 21 (5), pp. e0347860. Date of Electronic Publication: 2026 May 13 (Print Publication: 2026).
Publication Type: Journal Article
Journal Info: Publisher: Public Library of Science Country of Publication: United States NLM ID: 101285081 Publication Model: eCollection Cited Medium: Internet ISSN: 1932-6203 (Electronic) Linking ISSN: 19326203 NLM ISO Abbreviation: PLoS One Subsets: MEDLINE
Database: MEDLINE Ultimate
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  Data: <searchLink fieldCode="AU" term="%22Cao+Y%22">Cao Y</searchLink>; School of Computer Science and Engineering, Shenyang Jianzhu University, Shenyang, China.; Liaoning Provincial Key Laboratory of Big Data Management and Analysis of Urban Construction, Shenyang, China.; Shenyang Branch of National Special Computer Engineering Technology Research Center, Shenyang, China.<br /><searchLink fieldCode="AU" term="%22Wu+B%22">Wu B</searchLink>; School of Computer Science and Engineering, Shenyang Jianzhu University, Shenyang, China.; Liaoning Provincial Key Laboratory of Big Data Management and Analysis of Urban Construction, Shenyang, China.; Shenyang Branch of National Special Computer Engineering Technology Research Center, Shenyang, China.<br /><searchLink fieldCode="AU" term="%22Wen+M%22">Wen M</searchLink>; School of Computer Science and Engineering, Shenyang Jianzhu University, Shenyang, China.; Liaoning Provincial Key Laboratory of Big Data Management and Analysis of Urban Construction, Shenyang, China.; Shenyang Branch of National Special Computer Engineering Technology Research Center, Shenyang, China.
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  Data: <searchLink fieldCode="JN" term="%22101285081%22">PloS one</searchLink> [PLoS One] 2026 May 13; Vol. 21 (5), pp. e0347860. <i>Date of Electronic Publication: </i>2026 May 13 (<i>Print Publication: </i>2026).
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        Value: 10.1371/journal.pone.0347860
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              Text: 2026 May 13
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