Gazi University Journal of Science - Journal - Bridge of Knowledge

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Gazi University Journal of Science

ISSN:

1303-9709

eISSN:

2147-1762

Disciplines
(Field of Science):

  • Ethnology and cultural anthropology (Humanities)
  • History (Humanities)
  • Biomedical engineering (Engineering and Technology)
  • Civil engineering, geodesy and transport (Engineering and Technology)
  • Materials engineering (Engineering and Technology)
  • Mechanical engineering (Engineering and Technology)
  • Medical biology (Medical and Health Sciences )
  • Health sciences (Medical and Health Sciences )
  • Family studies (Family studies)
  • Agriculture and horticulture (Agricultural sciences)
  • Law (Social studies)
  • International relations (Social studies)
  • Biotechnology (Natural sciences)
  • Mathematics (Natural sciences)
  • Physical sciences (Natural sciences)

Ministry points: Help

Ministry points - current year
Year Points List
Year 2024 20 Ministry scored journals list 2024
Ministry points - previous years
Year Points List
2024 20 Ministry scored journals list 2024
2023 20 Ministry Scored Journals List
2022 20 Ministry Scored Journals List 2019-2022
2021 20 Ministry Scored Journals List 2019-2022
2020 20 Ministry Scored Journals List 2019-2022
2019 20 Ministry Scored Journals List 2019-2022

Model:

Open Access

Points CiteScore:

Points CiteScore - current year
Year Points
Year 2022 1.4
Points CiteScore - previous years
Year Points
2022 1.4
2021 1.1
2020 1.1
2019 0.8
2018 0.6
2017 0.5
2016 0.3
2015 0.5
2014 0.7
2013 0.6
2012 0.5
2011 0.3

Impact Factor:

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total: 2

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Catalog Journals

Year 2022
  • Using Long-Short term Memory networks with Genetic Algorithm to predict engine condition
    Publication

    - Gazi University Journal of Science - Year 2022

    Predictive maintenance (PdM) is a type of approach for maintenance processes, allowing maintenance actions to be managed depending on the machine's current condition. Maintenance is therefore carried out before failures occur. The approach doesn’t only help avoid abrupt failures but also helps lower maintenance cost and provides possibilities to manufacturers to manage maintenance budgets in a more efficient way. A new deep neural...

    Full text to download in external service

Year 2016

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