Comparison between artificial neural network and linear model prediction performance for FDI disparity and the growth rate of companies in Hungarian counties Online publication date: Thu, 10-Aug-2023
by Devesh Singh
International Journal of Business Information Systems (IJBIS), Vol. 43, No. 4, 2023
Abstract: Artificial neural network (ANN) is a growing concept in economics. The objective of this article is to compare the prediction performance of FDI inflow in companies and the growth rate of the companies in Hungarian counties through linear and ANN model. This article examines the regional level data of GDP per capita, urbanisation, market share of foreign investment received companies, labour productivity and agglomeration over the period of 2001 to 2018. Further, this article used the RStudio platform to analyse the data with resilient backpropagation with weight backtracking algorithm and root mean square error to check the predictability performance between ANN and linear model. The result suggests that ANN has an ability to converge, generalised and learns the growth rate of companies and FDI disparities for forecasting. The scatter plot of performance comparison depicts, ANN framework has better efficiency of forecast compared to the linear model.
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Business Information Systems (IJBIS):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email subs@inderscience.com
Our Blog 
Follow us on Twitter 
Visit us on Facebook