An Artificial Neural Network Model for a Wholesale Company’s Order-cycle Management

Kód výsledku v 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>

Výsledek na webu

<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>

Jazyk výsledku

angličtina

Název v původním jazyce

An Artificial Neural Network Model for a Wholesale Company’s Order-cycle Management

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

An Artificial Neural Network Model for a Wholesale Company’s Order-cycle Management

Popis výsledku anglicky

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.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

50602 - Public administration

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2016

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

International Journal of Engineering Business Management

ISSN

1847-9790

e-ISSN

—

Svazek periodika

2016

Číslo periodika v rámci svazku

8

Stát vydavatele periodika

HR - Chorvatská republika

Počet stran výsledku

6

Strana od-do

1-6

Kód UT WoS článku

000381868600001

EID výsledku v databázi Scopus

2-s2.0-84995532106