ARTIFICIAL INTELLIGENCE IN ARCHITECTURE: A COMPREHENSIVE REVIEW OF DEEP LEARNING ARCHITECTURES, GENERATIVE SYSTEMS, AND DATA-DRIVEN DESIGN PARADIGMS IN THE BUILT ENVIRONMENT

Öz

Artificial Intelligence (AI) has emerged as a transformative paradigm in architecture, influencing design processes, decision-making mechanisms, and knowledge production. This study aims to provide a comprehensive review of AI applications in architecture by analyzing 44 academic studies within the framework of deep learning architectures, generative systems, data-driven design approaches, optimization strategies, and theoretical transformations. The research adopts a qualitative and thematic analysis methodology, classifying the literature based on methods, application areas, and key findings. The results reveal a strong concentration of research on deep learning architectures, particularly Convolutional Neural Networks (CNNs), which demonstrate high accuracy in visual analysis and classification tasks. In contrast, Recurrent Neural Networks (RNNs) and their variants show emerging potential in temporal and process-oriented applications. Additionally, generative models such as Generative Adversarial Networks (GANs) are identified as a turning point, enabling the transition from analytical to generative design processes. The findings also highlight the growing role of data-driven and performance-oriented approaches in optimizing architectural decision-making, alongside increasing emphasis on model efficiency and scalability. The study concludes that AI in architecture is evolving from a technical tool into a multidimensional paradigm that reshapes design thinking and practice. It further suggests that future research should focus on hybrid AI systems, real-time adaptive design, and the integration of AI literacy into architectural education.

Anahtar Kelimeler

• Artificial Intelligence
• Deep Learning
• Generative Design
• Data-Driven Architecture
• Architectural Design Processe

Etik Beyan

The authors declares that there is no conflict of interest regarding the publication of this study.

Mimarlıkta Yapay Zekâ: Yapılı Çevrede Derin Öğrenme Mimarileri, Üretken Sistemler ve Veri Odaklı Tasarım Paradigmalarının Kapsamlı Bir İncelemesi

Öz

Yapay Zekâ (YZ), mimarlık alanında tasarım süreçlerini, karar verme mekanizmalarını ve bilgi üretimini etkileyen dönüştürücü bir paradigma olarak ortaya çıkmıştır. Bu çalışma, derin öğrenme mimarileri, üretken sistemler, veri odaklı tasarım yaklaşımları, optimizasyon stratejileri ve kuramsal dönüşümler çerçevesinde 44 akademik çalışmayı inceleyerek mimarlıkta yapay zekâ uygulamalarına ilişkin kapsamlı bir değerlendirme sunmayı amaçlamaktadır. Araştırma, yöntemler, uygulama alanları ve temel bulgular doğrultusunda literatürü sınıflandıran nitel ve tematik analiz metodolojisini benimsemektedir. Sonuçlar, özellikle görsel analiz ve sınıflandırma görevlerinde yüksek doğruluk sağlayan Evrişimsel Sinir Ağları (CNN) başta olmak üzere derin öğrenme mimarilerine yönelik güçlü bir araştırma yoğunluğu olduğunu ortaya koymaktadır. Buna karşılık, Tekrarlayan Sinir Ağları (RNN) ve türevleri, zamansal ve süreç odaklı uygulamalarda gelişmekte olan bir potansiyel göstermektedir. Ayrıca, Üretken Çekişmeli Ağlar (GAN) gibi üretken modellerin, analitik tasarım süreçlerinden üretken tasarım süreçlerine geçişi mümkün kılarak önemli bir dönüm noktası oluşturduğu belirlenmiştir. Bulgular, mimari karar verme süreçlerinin optimize edilmesinde veri odaklı ve performans temelli yaklaşımların giderek artan rolünü ve bunun yanında model verimliliği ile ölçeklenebilirliğe verilen önemin yükseldiğini de göstermektedir. Çalışma, mimarlıkta yapay zekânın yalnızca teknik bir araç olmaktan çıkarak tasarım düşüncesini ve uygulamalarını yeniden şekillendiren çok boyutlu bir paradigma hâline geldiği sonucuna ulaşmaktadır. Ayrıca gelecekteki araştırmaların hibrit yapay zekâ sistemleri, gerçek zamanlı uyarlanabilir tasarım ve yapay zekâ okuryazarlığının mimarlık eğitimine entegrasyonu üzerine odaklanması gerektiğini önermektedir.

Anahtar Kelimeler

• Yapay Zekâ
• Derin Öğrenme
• Üretken Tasarım
• Veri Odaklı Mimarlık
• Mimari Tasarım Süreçleri

Etik Beyan

Yazarlar, bu çalışmanın yayımlanmasıyla ilgili herhangi bir çıkar çatışması bulunmadığını beyan eder.

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