بناء نموذج رياضي لتقدير قيمة المباني السكنية في سوريا (دمشق)

الموضوعات

علوم تطبيقية وتكنولوجية

روابط وملفات

التعريف والنوع

رقم الوثيقة

00bd25a8-36bc-4828-82b4-e4ae90bb587d

رقم العقد

0

نوع الوسائط

Crawler

نوع المحتوى

الرسائل العلمية

صيغة المصدر

رسائل دكتوراة

نوع الملف

pdf text

أسماء الملفات

1957970_1.pdf

بيانات النشر

ترجمة العنوان

Building A Mathematical Model To Estimate The Value Of Residential Buildings In Syria (Damascus)

ألقاب المؤلفين

[{"name_ar":"محمد نايفة","title_ar":"اشراف","title_en":"Supervision"},{"name_ar":"منى حمادة","title_ar":"اعداد","title_en":"Preparation"}]

اللغة

Arabic

المصدر والدورية

اسم المصدر

بناء نموذج رياضي لتقدير قيمة المباني السكنية في سوريا (دمشق)

المحتوى والصفحات

عدد الصفحات

286

ترجمة الملخص

Real estate valuation process is used to determine the real estate value which is essential for conducting mortgage,feasibility studies and other commercial and economical activities.The real estate valuation is the process of estimating the real estate price based on the real estate layout and property features and specifications, obviously the real estate estimated priceis affected by a set of determining factors and variables.The main aim of this research is to develop a mathematical model for real estate valuation in Syria, basically for residential buildings in Damascus.Based on the literature survey on the subject matter, a set of variables or determinants that affect the residential real estate values were defined A questionnaire was designed to identify thereality of the real estate valuation practice in Syria and to specify the basic variables affecting the value of residential property in Damascus.The collected data were analyzed using the SPSS package, so the variables which affect the value of residential property were arranged in order of their importance. It was found that the most important variables are: "the region", "the area (square meter)", "the security situation of the area", "the finishing level" , " the possibility of transfer of ownership","the Property View" and "the property zone type-is it commercial or residential” . Data analysis revealed that the degree of importance of 26% of the studied variables varies according to the beneficiary institution that the evaluator works for, and the degree of importance of 32% of the studied variables varies according to the responder experience. It was concluded that there are strong positive correlations between most of the studied variables in terms of their degree of importance. Based on these results,atotal of 114 sets of real estate evaluation data of residential properties in Damascus were collected from the banking sector (the yarehistorically defined by experts and were used for mortgage). These collected sets of data were analyzed and used to develop and test a set of models based on various methods (multiple linear regression, multiple non-linear regression, artificial neural networks) and a model based on the average results of those models. Then, a comparison between these models was carried out based on a set of criteria (i.e. Mean Absolute Error, Mean Absolute Percentage Error, the correlation coefficient, Multiple Coefficient of determination and the percentage of cases where the Percentage of absolute error is less than 5%). The results revealed that the predictive performance of the multiple non-linear regression model forreal estate valuation of residential buildings in Damascus is the best compared to other models‟ performance. Furthermore, the multiple non-linear regression model demonstrates logical behavior toward the change of variables within the model structure

كلمات الباحثين

Artificial Neural Networks, Multiple Regression Analysis, real estate valuation, الشبكات العصبونية الاصطناعية, المباني السكنية, تحليل الانحدار, تقييم العقارات, دمشق, سورية (دمشق), نموذج رياضي

إشراف وإعداد

الإشراف

محمد نايفة

الإعداد

منى حمادة

الاقتباسات الببليوغرافية