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An Improved Neural Approaches for Forecasting Demand in Supply Chain Management

by Mariem Mrad, Younes Boujelbene
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 182 - Number 50
Year of Publication: 2019
Authors: Mariem Mrad, Younes Boujelbene
10.5120/ijca2019918766

Mariem Mrad, Younes Boujelbene . An Improved Neural Approaches for Forecasting Demand in Supply Chain Management. International Journal of Computer Applications. 182, 50 ( Apr 2019), 44-51. DOI=10.5120/ijca2019918766

@article{ 10.5120/ijca2019918766,
author = { Mariem Mrad, Younes Boujelbene },
title = { An Improved Neural Approaches for Forecasting Demand in Supply Chain Management },
journal = { International Journal of Computer Applications },
issue_date = { Apr 2019 },
volume = { 182 },
number = { 50 },
month = { Apr },
year = { 2019 },
issn = { 0975-8887 },
pages = { 44-51 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume182/number50/30543-2019918766/ },
doi = { 10.5120/ijca2019918766 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:14:56.974189+05:30
%A Mariem Mrad
%A Younes Boujelbene
%T An Improved Neural Approaches for Forecasting Demand in Supply Chain Management
%J International Journal of Computer Applications
%@ 0975-8887
%V 182
%N 50
%P 44-51
%D 2019
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Demand forecasting plays a pivotal role for supply chain management. It allows predicting and meeting future demands of the product and expectations of customers. Several forecasting techniques have been developed, each one has its particular benefits and limitations compared to other approaches. This motivates the development of artificial neural networks (ANNs) to make intelligent decisions while taking advantage of today’s processing power. Well, this paper deals with an improved algorithm for feedforward neural networks. Initially, the neural modelling process will be discussed. The approach adopted of neural modeling will be presented in a second time; this method is based on mono-network neural modeling and multi-network neural modeling. The results of simulation obtained will be illustrated by a simulated time series data.

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Index Terms

Computer Science
Information Sciences

Keywords

Neural Networks Supply chain management Demand Forecasting Time series forecasting.

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