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Citation(s) in
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For:
Liu J
, Zhang S, Wu C, Liang J, Wang X, Teo KL.
A hybrid approach to constrained global optimization.
Appl Soft Comput
2016;
47
:281-94. [DOI:
10.1016/j.asoc.2016.05.021
]
[
Citation(s) in
RCA
: 15
]
[
Impact Index Per Article: 1.9
]
[
Reference Citation Analysis
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[Indexed: 11/20/2022]
Number
Cited by Other Article(s)
1
Zhao F
, Bao H, Wang L, He X, Jonrinaldi. A hybrid cooperative differential evolution assisted by CMA-ES with local search mechanism.
Neural Comput Appl
2022. [DOI:
10.1007/s00521-021-06849-z
]
[
Citation(s) in
RCA
: 0
]
[
Impact Index Per Article: 0
]
[
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[Indexed: 11/29/2022]
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2
Data allocation in distributed database systems: a novel hybrid method based on differential evolution and variable neighborhood search.
SN APPLIED SCIENCES
2019. [DOI:
10.1007/s42452-019-1787-3
]
[
Citation(s) in
RCA
: 3
]
[
Impact Index Per Article: 0.6
]
[
Reference Citation Analysis
]
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[Indexed: 11/26/2022]
Open
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3
A hybrid optimization approach based on clustering and chaotic sequences.
INT J MACH LEARN CYB
2019. [DOI:
10.1007/s13042-019-00979-6
]
[
Citation(s) in
RCA
: 16
]
[
Impact Index Per Article: 3.2
]
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[Indexed: 11/27/2022]
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4
A new hybrid optimization method combining artificial bee colony and limited-memory BFGS algorithms for efficient numerical optimization.
Appl Soft Comput
2018. [DOI:
10.1016/j.asoc.2018.06.010
]
[
Citation(s) in
RCA
: 30
]
[
Impact Index Per Article: 5.0
]
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[Indexed: 11/21/2022]
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5
Badem H
, Basturk A, Caliskan A, Yuksel ME. A new efficient training strategy for deep neural networks by hybridization of artificial bee colony and limited–memory BFGS optimization algorithms.
Neurocomputing
2017. [DOI:
10.1016/j.neucom.2017.05.061
]
[
Citation(s) in
RCA
: 75
]
[
Impact Index Per Article: 10.7
]
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Reference Citation Analysis
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[Indexed: 11/30/2022]
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