Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Blaž Kažič"'
Publikováno v:
Applied Sciences, Vol 11, Iss 15, p 6787 (2021)
Demand forecasting is a crucial component of demand management, directly impacting manufacturing companies’ planning, revenues, and actors through the supply chain. We evaluate 21 baseline, statistical, and machine learning algorithms to forecast s
Externí odkaz:
https://doaj.org/article/d200d8e0fbeb4083a53ac99e372e645c
Publikováno v:
Sensors, Vol 19, Iss 8, p 1955 (2019)
To achieve the full analytical potential of the streaming data from the internet of things, the interconnection of various data sources is needed. By definition, those sources are heterogeneous and their integration is not a trivial task. A common ap
Externí odkaz:
https://doaj.org/article/fa047ce67f4b48dd9278b7a8b65fa0d3
Publikováno v:
Applied Sciences, Vol 11, Iss 6787, p 6787 (2021)
Applied Sciences
Volume 11
Issue 15
Applied Sciences
Volume 11
Issue 15
Demand forecasting is a crucial component of demand management, directly impacting manufacturing companies’ planning, revenues, and actors through the supply chain. We evaluate 21 baseline, statistical, and machine learning algorithms to forecast s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e9e4984054619076cf9f7eb409ad2a3a
https://doi.org/10.3390/app11156787
https://doi.org/10.3390/app11156787
Publikováno v:
Sensors, Vol 19, Iss 8, p 1955 (2019)
Sensors
Volume 19
Issue 8
Sensors (Basel, Switzerland)
Sensors
Volume 19
Issue 8
Sensors (Basel, Switzerland)
To achieve the full analytical potential of the streaming data from the internet of things, the interconnection of various data sources is needed. By definition, those sources are heterogeneous and their integration is not a trivial task. A common ap
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8e657949b1971bc29ead63525d96d057
https://www.mdpi.com/1424-8220/19/8/1955
https://www.mdpi.com/1424-8220/19/8/1955
Publikováno v:
IEEE Access, Vol 5, Pp 27400-27420 (2017)
Made possible by the availability of spatio-temporal data collected by smart phones and other smart devices, understanding people's mobility patterns has become one of the most promising locationbased services in the past few years, providing various
Externí odkaz:
https://doaj.org/article/05a8d8347c704c909f5ca1268aa20ad5
Publikováno v:
Scopus-Elsevier
VEHITS
VEHITS
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0dbee729f9eca59401d4ef53f2ea66b0
http://www.scopus.com/inward/record.url?eid=2-s2.0-84939550981&partnerID=MN8TOARS
http://www.scopus.com/inward/record.url?eid=2-s2.0-84939550981&partnerID=MN8TOARS
