Expanding the Application Models Box Jenkins, Artificial Neural Network and Adjusted Exponential forecasting Social Phenomena (Case study: forecasting of marriage and divorce in Ilam)

Subject Areas : Futurology

Mohammadreza  Omidi ¹ (Ph.D. in Industrial Engineering, Islamic Azad University, Tehran South Branch)
Nabi  Omidi ² (Instructor, Payam Noor University, Department of Management, Ilam, Iran.)
Ardeshir  Shiri ³ (Assistant Professor, University of Ilam, Department of Management, Ilam, Iran. (Corresponding Author) [e-mail])
Rahmatullah  Mohammadipour ⁴ (Assistant Professor, Islamic Azad University, Ilam Branch, Accounting Department, Ilam, Iran.)

Received: 2016-01-22 Accepted : 2016-08-05 Published : 2017-11-22

Keywords: marriage, Divorce, Forecasting, Box and Jenkins Models, Artificial Neural Network, Time series,

Abstract :

One of the most important tools in the hands of managers and experts to make strategic decisions is Methods of forecasting and futures. Despite the development of prediction methods, but less likely to use these methods in predicting social phenomena such as marriage, divorce and population growth are discussed. In this study, using data from marriage and divorce between the years 1992 to 2013 in Ilam province to forecasts, the number of these phenomena using models Box Jenkins, Artificial Neural Network and Adjusted Exponential has been studied for years to come. The results showed that the prediction accuracy Box Jenkins model to predict the number of marriages and Artificial Neural Network model to predict the number of divorces is more than any other prediction methods. The predicted values showed that the proportion of marriages end in divorce in Ilam province between the years 2014 to 2018 following the gentle slope, to reduce the move.