Zobrazeno 1 - 3
of 3
pro vyhledávání: '"Tahar Ouhrouche"'
Autor:
Fatima Zohra Benhamida, Ouahiba Kaddouri, Tahar Ouhrouche, Mohammed Benaichouche, Diego Casado-Mansilla, Diego Lopez-de-Ipina
Publikováno v:
Journal of Communications Software and Systems, Vol 17, Iss 2, Pp 185-196 (2021)
With the availability of data and the increasing capabilities of data processing tools, many businesses are leveraging historical sales and demand data to implement smart inventory management systems. Demand forecasting is the process of estimating t
Externí odkaz:
https://doaj.org/article/447e499300734590bc5d64a29bc7a6f3
Autor:
Diego Casado-Mansilla, Tahar Ouhrouche, Mohammed Benaichouche, Ouahiba Kaddouri, Diego López-de-Ipiña, Fatima Zohra Benhamida
Publikováno v:
Journal of Communications Software and Systems, Vol 17, Iss 2, Pp 185-196 (2021)
Journal of Communications Software and Systems
Volume 17
Issue 2
Journal of Communications Software and Systems
Volume 17
Issue 2
With the availability of data and the increasing capabilities of data processing tools, many businesses are leveraging historical sales and demand data to implement smart inventory management systems. Demand forecasting is the process of estimating t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e0ab16886539f17a669d822c2164fff0
https://jcoms.fesb.unist.hr/10.24138/jcomss-2021-0068/
https://jcoms.fesb.unist.hr/10.24138/jcomss-2021-0068/
Autor:
Diego Casado-Mansilla, Tahar Ouhrouche, Diego López-de-Ipiña, Mohamed Benaichouche, Fatima Zohra Benhamida, Ouahiba Kaddouri
Publikováno v:
2020 5th International Conference on Smart and Sustainable Technologies (SpliTech).
Demand forecasting is playing a crucial role for many retail firms where effective inventory management allows accurate balance between demands and offers. One of the most common methods for demand forecasting is by analyzing previous data to help pr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f9707579734fa4dd8406032f01db2774
https://doi.org/10.23919/splitech49282.2020.9243824
https://doi.org/10.23919/splitech49282.2020.9243824