Suchergebnisse - "Multi-objective evolution algorithm"
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Autoren:
Quelle: IET Collaborative Intelligent Manufacturing. 7
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Autoren: et al.
Quelle: IEEE Access, Vol 9, Pp 1556-1574 (2021)
Schlagwörter: actuator and sensor fault, 0209 industrial biotechnology, multi-objective problems (MOP), missile guidance system, 0202 electrical engineering, electronic engineering, information engineering, Electrical engineering. Electronics. Nuclear engineering, 02 engineering and technology, Takagi-Sugeno (T-S) fuzzy systems, observer-based fault tolerant control, Reverse-order multi-objective evolution algorithm (MOEA), TK1-9971
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Autoren: et al.
Quelle: Interdisciplinary Sciences: Computational Life Sciences. 16:519-531
Schlagwörter: Models, Molecular, Deep Learning, Protein Conformation, Proteins, Humans, Computational Biology, Algorithms
Zugangs-URL: https://pubmed.ncbi.nlm.nih.gov/38190097
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Autoren: et al.
Quelle: Soft Computing. 26:12077-12092
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Optimal allocation of microgrid using a differential multi-agent multi-objective evolution algorithm
Autoren: et al.
Quelle: Applied Mathematics and Nonlinear Sciences. 6:111-124
Schlagwörter: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology, 7. Clean energy
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Autoren: et al.
Quelle: Interdisciplinary sciences, computational life sciences [Interdiscip Sci] 2024 Sep; Vol. 16 (3), pp. 519-531. Date of Electronic Publication: 2024 Jan 08.
Publikationsart: Journal Article
Info zur Zeitschrift: Publisher: Springer-Verlag Country of Publication: Germany NLM ID: 101515919 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1867-1462 (Electronic) Linking ISSN: 18671462 NLM ISO Abbreviation: Interdiscip Sci Subsets: MEDLINE
MeSH-Schlagworte: Algorithms* , Protein Conformation* , Proteins*/chemistry, Humans ; Computational Biology/methods ; Models, Molecular ; Deep Learning
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Autoren:
Quelle: 2008 International Conference on Information and Automation. :1188-1192
Schlagwörter: 0209 industrial biotechnology, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology
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Quelle: 2018 5th International Conference on Electrical & Electronics Engineering and Computer Science (ICEEECS 2018).
Zugangs-URL: http://webofproceedings.org/proceedings_series/ECS/ICEEECS 2018/ICEEECS_0613054.pdf
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Autoren: et al.
Quelle: Scientific Reports, Vol 15, Iss 1, Pp 1-12 (2025)
Schlagwörter: Water inrush, Fluid‒mechanical coupling effect, Cable, Optimization, CMOEAD (constrained multi-objective evolution algorithm based on decomposition) algorithm, Medicine, Science
Dateibeschreibung: electronic resource
Relation: https://doaj.org/toc/2045-2322
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Autoren: Bixin Hu
Quelle: 2011 Fifth International Conference on Genetic and Evolutionary Computing.
Schlagwörter: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology, 0101 mathematics, 01 natural sciences
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Autoren: et al.
Quelle: BMC Bioinformatics
BMC Bioinformatics, Vol 10, Iss 1, p 101 (2009)Schlagwörter: Models, Molecular, 0301 basic medicine, 0303 health sciences, Databases, Factual, QH301-705.5, Methodology Article, Computer applications to medicine. Medical informatics, R858-859.7, Molecular Conformation, Biochemistry, Computer Science Applications, 03 medical and health sciences, Drug Design, Computer Simulation, Biology (General), Molecular Biology, Algorithms, Software
Zugangs-URL: https://bmcbioinformatics.biomedcentral.com/track/pdf/10.1186/1471-2105-10-101
https://pubmed.ncbi.nlm.nih.gov/19335906
https://doaj.org/article/07286cc5271d44d4817a35718b243511
https://bmcbioinformatics.biomedcentral.com/articles/10.1186/1471-2105-10-101
https://doi.org/10.1186/1471-2105-10-101
https://doaj.org/article/07286cc5271d44d4817a35718b243511
https://link.springer.com/article/10.1186%2F1471-2105-10-101
https://www.ncbi.nlm.nih.gov/pubmed/19335906
https://link.springer.com/content/pdf/10.1186%2F1471-2105-10-101.pdf -
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Autoren: et al.
Quelle: Journal of Physics: Conference Series. 753:062007
Schlagwörter: 0211 other engineering and technologies, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology, 7. Clean energy
Zugangs-URL: https://iopscience.iop.org/article/10.1088/1742-6596/753/6/062007/pdf
http://ui.adsabs.harvard.edu/abs/2016JPhCS.753f2007W/abstract
http://iopscience.iop.org/article/10.1088/1742-6596/753/6/062007/pdf
https://google.iopscience.iop.org/article/10.1088/1742-6596/753/6/062007
https://iopscience.iop.org/article/10.1088/1742-6596/753/6/062007
https://google.iopscience.iop.org/article/10.1088/1742-6596/753/6/062007/pdf -
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Autoren: et al.
Quelle: Management System Engineering, Vol 2, Iss 1, Pp 1-13 (2023)
Schlagwörter: Major public health emergencies, Medical supplies distribution, Multi-objective evolution algorithm, Urgency of demand, Management information systems, T58.6-58.62
Dateibeschreibung: electronic resource
Relation: https://doaj.org/toc/2731-5843
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Autoren: et al.
Quelle: Soft Computing - A Fusion of Foundations, Methodologies & Applications; Nov2022, Vol. 26 Issue 22, p12077-12092, 16p
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Autoren: et al.
Schlagwörter: environmental economic dispatch, Environmental economics (natural resource models, harvesting, pollution, etc.), multi-objective optimization, particle swarm optimization, adaptive space partition, Approximation methods and heuristics in mathematical programming, Multi-objective and goal programming
Dateibeschreibung: application/xml
Zugangs-URL: https://zbmath.org/6611237
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Autoren: et al.
Quelle: Methods. May2023, Vol. 213, p42-49. 8p.
Schlagwörter: *EVOLUTIONARY algorithms, *FEATURE selection, *GENE regulatory networks, *GENE expression, *DISEASE progression, *THERAPEUTICS
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Autoren: et al.
Weitere Verfasser: et al.
Schlagwörter: Hyperspectral classification, Hyperspectral pansharpening, Multi-objective evolution algorithm, Multi-task learning
Dateibeschreibung: ELETTRONICO
Relation: info:eu-repo/semantics/altIdentifier/wos/WOS:001221668500001; volume:108; journal:INFORMATION FUSION; https://hdl.handle.net/11571/1504916
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Autoren: et al.
Weitere Verfasser: et al.
Quelle: Information Fusion. 108:102383
Schlagwörter: Hyperspectral classification, Hyperspectral pansharpening, Multi-task learning, Multi-objective evolution algorithm
Dateibeschreibung: ELETTRONICO
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