استخدام الشبكات العصبية الاصطناعية لتصور الفقر

Abstract EN

The second domain the role of statistics in securing the requirements of the future society The research aims to test the impact of social, demographic and economic variables on poverty in Jordan and analyze in depth and determine the most important factors affecting it, using the systems of neural networks as a tool to support the decision-making process through strategic.

The research was based on the data of the Household Expenditure and Income Survey for 2017 on a sample of 20,000 families distributed to all governorates of the Kingdom and represented by nationality for Jordanian and non-Jordanian.

In this research, several factors affecting the incidence of family in poverty were studied.

However, this research showed that the statistical significance of the household size variable ranked first in the effect on the dependent variable (poverty rate).

The second variable was the level of household expenditure on food and non-food and services) in terms of importance in influencing (poverty rate), while the income variable came in third.

The research concludes that it is necessary to work to educate members of society about the dangers of high fertility rates, the dangers of frequent and congenital reproduction on the health of the mother and child in general, and raise awareness of poor families, family planning and reproductive planning in particular, as well as to work to create job opportunities for the poor as the high the level of per capita income is considered a manifestation of development.

The higher the income, the lower the number of deaths, and vice versa.

Improving the level of income delays the age of marriage, low fertility and improves the standard of living of poor families.

It also reduces the possibility of them falling into poverty.

We must work to improve their educational level, as education and raising its level delays marriage and brings it out of poverty.