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Shuffled Complex-Self Adaptive Hybrid EvoLution (SC-SAHEL) optimization framework

Crossref DOI link: https://doi.org/10.1016/j.envsoft.2018.03.019

Published Print: 2018-06

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Authors

Rahnamay Naeini, Matin

Yang, Tiantian

Sadegh, Mojtaba https://orcid.org/0000-0003-1775-5445
AghaKouchak, Amir https://orcid.org/0000-0003-4689-8357
Hsu, Kuo-lin

Sorooshian, Soroosh

Duan, Qingyun https://orcid.org/0000-0001-9955-1512
Lei, Xiaohui
Funding

Funding for this research was provided by:

U.S. Department of Energy (DE-IA0000018)

California Energy Commission (300-15-005)

NSF CyberSEES Project (CCF-1331915)

NOAA/NESDIS/NCDC (NA09NES4400006)

NCSU CICS (2009-1380-01)

U.S. Army Research Office (W911NF-11-1-0422)
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This article is maintained by: Elsevier

Article Title: Shuffled Complex-Self Adaptive Hybrid EvoLution (SC-SAHEL) optimization framework

Journal Title: Environmental Modelling & Software

CrossRef DOI link to publisher maintained version: https://doi.org/10.1016/j.envsoft.2018.03.019

Content Type: article

Copyright: © 2018 Elsevier Ltd. All rights reserved.