Journal Article GSI-2020-00213

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Application of nature-inspired optimization algorithms and machine learning for heavy-ion synchrotrons

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2019
World Scientific Publ. Singapur

International journal of modern physics / A Particles and fields, gravitation, cosmology A 34(36), 1942019 () [10.1142/S0217751X19420193]

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Classification:

Contributing Institute(s):
  1. Accelerator Physics (APH)
  2. Atomphysik (ATP)
Research Program(s):
  1. 6G12 - FAIR (POF3-624) (POF3-624)
  2. 631 - Accelerator R & D (POF3-631) (POF3-631)
  3. 6211 - Extreme States of Matter: From Cold Ions to Hot Plasmas (POF3-621) (POF3-621)

Appears in the scientific report 2019
Database coverage:
Medline ; Clarivate Analytics Master Journal List ; Current Contents - Physical, Chemical and Earth Sciences ; Ebsco Academic Search ; IF < 5 ; JCR ; SCOPUS ; Science Citation Index ; Science Citation Index Expanded ; Web of Science Core Collection
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The record appears in these collections:
Private Institute collections > >TGF > >PRO > APH
Private Institute collections > >WGF > >RED > ATP
Document types > Articles > Journal Article
FAIR Project > Accelerator Physics
Workflow collections > Public records
APPA/MML > Atomic Physics
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 Record created 2020-02-04, last modified 2023-03-17