Comparison of artificial neural network and box-Jenkins models to predict the number of patients with hypertension in Kalar

Author

Ahmad, Layla A. A.

Source

Ibn al-Haitham Journal for Pure and Applied Science

Issue

Vol. 33, Issue 4 (31 Dec. 2020), pp.110-121, 12 p.

Publisher

University of Baghdad College of Education for Pure Science / Ibn al-Haitham

Publication Date

2020-12-31

Country of Publication

Iraq

No. of Pages

12

Main Topic

Diseases

Topics

Abstract EN

Artificial Neural Network (ANN) is widely used in many complex applications.

Artificial neural network is a statistical intelligent technique resembling the characteristic of the human neural network.

The prediction of time series from the important topics in statistical sciences to assist administrations in the planning and make the accurate decisions, so the aim of this study is to analysis the monthly hypertension in Kalar for the period (January 2011- June 2018) by applying an autoregressive –integrated- moving average model (ARIMA) and artificial neural networks and choose the best and most efficient model for patients with hypertension in Kalar through the comparison between neural networks and Box- Jenkins models on a data set for predict.

Comparisons between the models has been performed using Criterion indicator Akaike information Criterion, mean square of error, root mean square of error, and mean olute percentage error, concluding that the prediction for patients with hypertension by using artificial neural networks model is the best.

American Psychological Association (APA)

Ahmad, Layla A. A.. 2020. Comparison of artificial neural network and box-Jenkins models to predict the number of patients with hypertension in Kalar. Ibn al-Haitham Journal for Pure and Applied Science،Vol. 33, no. 4, pp.110-121.
https://search.emarefa.net/detail/BIM-977526

Modern Language Association (MLA)

Ahmad, Layla A. A.. Comparison of artificial neural network and box-Jenkins models to predict the number of patients with hypertension in Kalar. Ibn al-Haitham Journal for Pure and Applied Science Vol. 33, no. 4 (2020), pp.110-121.
https://search.emarefa.net/detail/BIM-977526

American Medical Association (AMA)

Ahmad, Layla A. A.. Comparison of artificial neural network and box-Jenkins models to predict the number of patients with hypertension in Kalar. Ibn al-Haitham Journal for Pure and Applied Science. 2020. Vol. 33, no. 4, pp.110-121.
https://search.emarefa.net/detail/BIM-977526

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references : p. 120-121

Record ID

BIM-977526