Page 53 - Çevre Şehir ve İklim Dergisi - Sayı 4

URBAN TRANSFORMATION FORECASTS WITH

ARTIFICIAL INTELLIGENCE BASED ALGORITHMS

Hacı Abdullah UÇAN-Tayfun DEDE-Sinan NACAR

ABSTRACT
Urban transformation is a design practice at the focus point of modern urban life. This phenomenon
provides the purpose of human life improvement by organizing it on an urban-based. Urban areas that
were established and developed depending on time, geographical features, and historical processes
usually have built against the engineering approaches, especially for economic excuses and follow an
uncontrolled and inadequate course, and progress in a physical, social, and economic environment
which is inappropriate for human life. To improve such cities and to design future cities that include
sustainable structures, urban transformation interventions are becoming inevitable. In addition, the
risk factor caused by millions of inappropriate buildings against disaster risk is an essential topic
that should take place in the concept of urban transformation planning and engineering studies in
Turkey. Because an essential reason that urban transformation practices can affect the economic
indicators of the future of Turkey. It is emphasized how making very realistic predictions is quite
important. Using the periodic economic data of the urban transformation applications in our country,
estimation models were created for the urban transformation process using regression and artificial
intelligence-based algorithms. Thus, by processing the predicted data as input, it will be possible to
make predictions of the urban transformation process in Turkey. In general, the ANN method gave
better estimates than the classical regression methods. When the prediction models are examined
in detail for the training, validation and test data sets, some models obtained by adding gray wolf
optimization to the ANN yielded better results than the models established with other methods. The
best estimation model was obtained by using the TreeNet method, with NS values of 0.62 for the
number of flats, 0.70 for the number of licenses and 0.67 for the surface area, according to the average
evaluation for the training, test and validation sets.
Keywords: Urban transformation, Regression Analysis, Artificial Intelligence-Based Algorithms,
Optimization, Prediction Models

Dr., T.C. Çevre Şehircilik ve İklim Değişikliği Bakanlığı, Tabiat Varlıklarını Koruma Genel Müdürlüğü
Mail: habdullah.ucan@csb.gov.tr
ORCID ID: https://orcid.org/0000-0001-9049-8858
Prof. Dr., Karadeniz Teknik Üniversitesi, İnşaat Mühendisliği bölümü
Mail: dtayfun@ktu.edu.tr
ORCID ID : https://orcid.org/0000-0001-9672-2232

Dr. Öğr. Üyesi, Tokat Gaziosmanpaşa Üniversitesi, İnşaat Mühendisliği bölümü
Mail: sinannacar@hotmail.com
ORCID ID : https://orcid.org/0000-0003-2497-5032
Makale Atıf Bilgisi: Uçan, H. A. - Dede, T. ve Nacar, S. (2023). “Yapay Zekâ Tabanlı
Algoritmalar ile Kentsel Dönüşüm Tahminlerinin Yapılması”.
Çevre, Şehir ve İklim Dergisi. Yıl: 2. Sayı: 4. ss. (38-69)
Makale Türü: Araştırma
Geliş Tarihi: 27.04.2023
Kabul Tarihi: 19.06.2023
Yayın Tarihi: 31.07.2023
Yayın Sezonu: Temmuz 2023

38 Çevre, Şehir ve İklim Dergisi Çevre, Şehir ve İklim Dergisi
Deprem ve Kentsel Dönüşüm | Temmuz 2023 | Sayı: 4