GCO4015

Evolutionary and neural computing

(IT)

B Nath and X Li

6 points + 4 hours per week + Second semester + Gippsland, distance + Prerequisites: GCO2802, GCO3815 or similar

Synopsis: Introduction to intelligent systems. Concepts of genetic operators such as crossover and mutation. Fitness functions, scaling and sampling in GAs. Numerical optimisation using genetic algorithms. Applications to scheduling problems and machine learning. Basic concepts of neural computing. Introduction to some types of neural networks: feedforward neural nets, autoassociative nets, self-organising nets and fuzzy and neurofuzzy systems, and applications to which they are suited. Design of neural computing applications and optimisation using an iterative approach. Basic concepts of simulated annealing and applications.

Assessment: Assignments: 60% + Examination (2 hours): 40%