The evaluation of rental amount of religious endowments by using geomatic techniques and machine learning algorithms Hilla Iraq

Abstract EN

The religious endowments are one of the important sources, which acquirehistorical, cultural, and economic importance in all countries of the world.

Inparticular, a religious endowment in Iraq includes several distributed real estatesand lands that usually require efficient management systems.

One of the mostimportant factors affecting the management of real estates that belong toreligious endowments is the rental amount of each real estate.

In general, theestimation of the rental of real estates can support the future development ofreligious endowments.

Governmental agencies are faced with some challenges inthe management of religious endowments in terms of rental pricing due tonumerous economic and geographic factors.

The rapid development of artificialintelligence systems and Geomatic techniques can present a framework for rentalamount estimation based on spatial and non-spatial factors.

In this study, amachine learning algorithm (Support Vector Regression) will be combined withGeographic Information System (GIS) to predict and evaluate the rental amountof real estates that belong to a religious institution in Iraq (Shiite endowment inHillah city).

The final results indicated that the proposed method achieved anoverall accuracy of 71% , a root mean square error of 0.2257 million Iraq, Dinar(IQD), and a correlation coefficient of 0.9272.

This study can be used as aneffective tool for the decision-makers to plan and manage the religiousendowments in developing countries.

The religious endowments are one of the important sources, which acquirehistorical, cultural, and economic importance in all countries of the world.

Inparticular, a religious endowment in Iraq includes several distributed real estatesand lands that usually require efficient management systems.

One of the mostimportant factors affecting the management of real estates that belong toreligious endowments is the rental amount of each real estate.

In general, theestimation of the rental of real estates can support the future development ofreligious endowments.

Governmental agencies are faced with some challenges inthe management of religious endowments in terms of rental pricing due tonumerous economic and geographic factors.

The rapid development of artificialintelligence systems and Geomatic techniques can present a framework for rentalamount estimation based on spatial and non-spatial factors.

In this study, amachine learning algorithm (Support Vector Regression) will be combined withGeographic Information System (GIS) to predict and evaluate the rental amountof real estates that belong to a religious institution in Iraq (Shiite endowment inHillah city).

The final results indicated that the proposed method achieved anoverall accuracy of 71% , a root mean square error of 0.2257 million Iraq, Dinar(IQD), and a correlation coefficient of 0.9272.

This study can be used as aneffective tool for the decision-makers to plan and manage the religiousendowments in developing countries.