ISSN:
0219-1377
eISSN:
0219-3116
Disciplines
(Field of Science):
- information and communication technology (Engineering and Technology)
- safety engineering (Engineering and Technology)
- biomedical engineering (Engineering and Technology)
- management and quality studies (Social studies)
- international relations (Social studies)
- computer and information sciences (Natural sciences)
(Field of Science)
Ministry points: Help
Year | Points | List |
---|---|---|
Year 2024 | 100 | Ministry scored journals list 2024 |
Year | Points | List |
---|---|---|
2024 | 100 | Ministry scored journals list 2024 |
2023 | 100 | Ministry Scored Journals List |
2022 | 100 | Ministry Scored Journals List 2019-2022 |
2021 | 100 | Ministry Scored Journals List 2019-2022 |
2020 | 100 | Ministry Scored Journals List 2019-2022 |
2019 | 100 | Ministry Scored Journals List 2019-2022 |
2018 | 35 | A |
2017 | 35 | A |
2016 | 30 | A |
2015 | 30 | A |
2014 | 35 | A |
2012 | 30 | A |
2011 | 30 | A |
2010 | 27 | A |
Model:
Hybrid
Points CiteScore:
Year | Points |
---|---|
Year 2022 | 6.1 |
Year | Points |
---|---|
2022 | 6.1 |
2021 | 5.9 |
2020 | 5.8 |
2019 | 5.2 |
2018 | 5.4 |
2017 | 4.4 |
2016 | 4.6 |
2015 | 4.5 |
2014 | 5.1 |
2013 | 5.2 |
2012 | 4.2 |
2011 | 4.6 |
Impact Factor:
Log in to see the Impact Factor.
Sherpa Romeo:
Papers published in journal
Filters
total: 2
Catalog Journals
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Ontology-based text convolution neural network (TextCNN) for prediction of construction accidents
PublicationThe construction industry suffers from workplace accidents, including injuries and fatalities, which represent a significant economic and social burden for employers, workers, and society as a whole.The existing research on construction accidents heavily relies on expert evaluations,which often suffer from issues such as low efficiency, insufficient intelligence, and subjectivity.However, expert opinions provided in construction...
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Cluster-based instance selection for machine classification
Publication
seen 306 times