Course Information

Course Name	Turkish	Mimari tasarımda esnek hesaplama yöntemleri
	English	Soft Computing Met.in Arc.Des.
Course Code	MBL 615E	Credit	Lecture (hour/week)	Recitation (hour/week)	Laboratory (hour/week)
Semester	-	3	3	-	-
Course Language		English
Course Coordinator		Aslı Kanan
Course Objectives		1. To introduce the notion of uncertainty in architectural design 2. To provide knowledge on machine learning 3. To provide knowledge on artificial neural networks, support vector machines, heuristic and nature based algorithms in architecture 4. To introduce applications of fuzzy logic and sets theory in the area of architecture and design 5. To analyse contemporary architectural design approaches through the course topics
Course Description		Basic concepts of soft computing, uncertainty in architecture; Modelling uncertainty, probabilistic reasoning, bayesian networks, Possibility theory, rough set theory, Dempster–Shafer theory and applications in architecture; Fuzzy logic, fuzzy set theory and applications in architecture; Non-linear mathematics and dynamic systems; Chaotic systems, complexity, bifurcation theory and applications in architecture; Artificial neural networks, learning by back-propagation and applications in architecture; Unsupervised learning, self-organizing map, adaptive resonance theory and applications in architecture; Support vector machines and applications in architecture; Genetic algorithms and applications in architecture; Metaheuristic approach, particle swarm optimization, local search algorithms and applications in architecture
Course Outcomes		Students who successfully pass this course gain knowledge, skills and proficiency in the following subjects: 1. Different mathematical treatments of uncertainty 2. Fuzzy logic method and its applications in architecture 3. How to model architectural chaotic systems 4. The basics of neural networks and their applications in architecture 5. Support vector machines and their applications in architecture 6. The use of local search algorithms and simple heuristics in architecture 7. Which soft computing method is suitable for a design problem embedded in uncertainty, heuristics and natural language
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