An Artificial Neural Network Model for a Wholesale Company’s Order-cycle Management
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26510%2F16%3APU119404" target="_blank" >RIV/00216305:26510/16:PU119404 - isvavai.cz</a>
Result on the web
<a href="http://www.intechopen.com/journals/international_journal_of_engineering_business_management/an-artificial-neural-network-model-for-the-wholesale-company-order-s-cycle-management" target="_blank" >http://www.intechopen.com/journals/international_journal_of_engineering_business_management/an-artificial-neural-network-model-for-the-wholesale-company-order-s-cycle-management</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.5772/3" target="_blank" >10.5772/3</a>
Alternative languages
Result language
angličtina
Original language name
An Artificial Neural Network Model for a Wholesale Company’s Order-cycle Management
Original language description
The purpose of this article is to verify the possibility of using artificial neural networks (ANN) in business management processes, primarily in the area of supply chain management. The author has designed several neural network models featuring different architectures to optimize the level of the company’s inventory. The results of the research show that ANN can be used for managing a company’s order cycle and lead to reduced levels of goods purchased and storage costs. Optimal neural networks show suitable results for subsequent prediction of the amount of items to be ordered and for achieving reduced inventory purchase and keeping costs down.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
50602 - Public administration
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2016
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
International Journal of Engineering Business Management
ISSN
1847-9790
e-ISSN
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Volume of the periodical
2016
Issue of the periodical within the volume
8
Country of publishing house
HR - CROATIA
Number of pages
6
Pages from-to
1-6
UT code for WoS article
000381868600001
EID of the result in the Scopus database
2-s2.0-84995532106