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Comparison Between the Main Façades Facing the Main Courtyards of Traditional Houses in Sulaymaniyah and Sanandaj Cities

Year: 2026
Type: article
Abstract: Traditional Kurdish architecture in the cities of Sulaymaniyah and Sanandaj represents a living mirror of social and cultural identity, with houses with main courtyards forming the heart of residential life, and the facades overlooking them becoming the most prominent symbolic and aesthetic elements. Despite the claim that there is a fundamental similarity between the facades of the two cities, this claim has remained without rigorous scientific tests, creating a knowledge gap that hindered the determination of the nature of the relationship. This research seeks to bridge this gap through an authentic analytical framework. The first phase relied on a descriptive analysis of the formative elements across the three levels (lower, middle, and upper), and led to the discovery of architectural elements without previous names, and the formulation of authentic Kurdish names for them for the first time. The second phase focused on transforming the elements of composition and facade materials from traditional descriptions to measurable quantitative-compositional indicators, within an analytical system developed in the Python/Jupyter Notebook environment. This framework made it possible to encode formative elements in a digital "interface language" through automated mechanisms to recognize arcs, rhythms, and style consistency, while incorporating artificial intelligence as a supporting tool for both formative and cognitive reading of the interface. The results showed a structural and physical convergence between the interfaces, while the perceptual-visual reading revealed a gap between the computational and the perceptual, which led to the formulation of the concept of "false similarity" to explain the ambiguous relationship between the physical and the visual in traditional.
DOI: 10.17656/sjes.10203
Language: English
Subfield: Archeology
Open Access status: diamond
OpenAlex ID: W7154010782
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