Abstract
The religious endowments are one of the important sources, which acquire historical, cultural, and economic importance in all countries of the world. In particular, a religious endowment in Iraq includes several distributed real estates and lands that usually require efficient management systems. One of the most important factors affecting the management of real estates that belong to religious endowments is the rental amount of each real estate. In general, the estimation of the rental of real estates can support the future development of religious endowments. Governmental agencies are faced with some challenges in the management of religious endowments in terms of rental pricing due to numerous economic and geographic factors. The rapid development of artificial intelligence systems and Geomatic techniques can present a framework for rental amount estimation based on spatial and non-spatial factors. In this study, a machine learning algorithm (Support Vector Regression) will be combined with Geographic Information System (GIS) to predict and evaluate the rental amount of real estates that belong to a religious institution in Iraq (Shiite endowment in Hillah city). The final results indicated that the proposed method achieved an overall 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 an effective tool for the decision-makers to plan and manage the religious endowments in developing countries.
Highlights
In the planning concept, the concept of rent is defined as the amount of money that tenants are willing to pay for a specific real estate in terms of the geographic location and other characteristics such as land use and structural condition [1]
This study presents integration between machine learning algorithm and Geographic Information System (GIS) modeling to estimate and evaluate the rental amount of real estates that belong to a religious institution in Iraq (Shiite endowment in Hilla city)
In order to predict a rental amount of each real estate within endowments properties by Iraqi Dinar (IQD), we can use this function
Summary
The concept of rent is defined as the amount of money that tenants are willing to pay for a specific real estate in terms of the geographic location and other characteristics such as land use and structural condition [1]. Spatial modeling has attracted the experts in the field of real estate development, due to its significant capabilities that combined geographical and statistical factors. Spatial modeling can evaluate the existing rent in terms of the influencing structural and geographical factors [3]. The estimation of rental amount can efficiently support the future development of religious endowments. Many countries such as Iraq started to develop digital databases that include religious endowments information (lands and real estate). This study presents integration between machine learning algorithm and GIS modeling to estimate and evaluate the rental amount of real estates that belong to a religious institution in Iraq (Shiite endowment in Hilla city)
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