Data Mining-Based Prediction of Manufacturing Situations. Issue 11 (2018)
- Record Type:
- Journal Article
- Title:
- Data Mining-Based Prediction of Manufacturing Situations. Issue 11 (2018)
- Main Title:
- Data Mining-Based Prediction of Manufacturing Situations
- Authors:
- Dolgui, A.
Bakhtadze, N.
Pyatetsky, V.
Sabitov, R.
Smirnova, G.
Elpashev, D.
Zakharov, E. - Abstract:
- Abstract: The paper proposes an approach to the early detection of factors implying the need in production schedule update. Resource state prediction methods are based on the development of a binary model and a machine learning techniques called association rules search.
- Is Part Of:
- IFAC-PapersOnLine. Volume 51:Issue 11(2018)
- Journal:
- IFAC-PapersOnLine
- Issue:
- Volume 51:Issue 11(2018)
- Issue Display:
- Volume 51, Issue 11 (2018)
- Year:
- 2018
- Volume:
- 51
- Issue:
- 11
- Issue Sort Value:
- 2018-0051-0011-0000
- Page Start:
- 316
- Page End:
- 321
- Publication Date:
- 2018
- Subjects:
- data mining -- knowledgebase -- association rule learning -- production scheduling -- productive resources
Automatic control -- Periodicals
629.805 - Journal URLs:
- https://www.journals.elsevier.com/ifac-papersonline/ ↗
http://www.sciencedirect.com/ ↗ - DOI:
- 10.1016/j.ifacol.2018.08.302 ↗
- Languages:
- English
- ISSNs:
- 2405-8963
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 7228.xml