MBL 615E - Soft Computing Met.in Arc.Des.

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