6 points, SCA Band 2, 0.125 EFTSL
Undergraduate - Unit
Refer to the specific census and withdrawal dates for the semester(s) in which this unit is offered.
Faculty
Coordinator(s)
S Parasuraman (Malaysia)
Unit guides
Synopsis
This unit provides a systematic approach of solving a variety of engineering problems using artificial intelligence techniques including fuzzy logic, artificial neural networks and genetic algorithms. The theory and applications of these soft computing techniques will be considered. Students will learn AI methods of problem solving. The AI language LISP will be introduced. The Matlab fuzzy logic, neural network and genetic algorithm toolboxes will be used to solve engineering problems.
Outcomes
The aim of this unit is to introduce the principles of artificial intelligence and soft computing techniques and shows how these techniques can be applied to solve a wide variety of engineering problems. Students will develop an understanding of and confidence in applying such artificial intelligence techniques as neural networks, fuzzy logic systems and genetic algorithms.
Assessment
Mid semester test: 10% + Practice assessment(lab): 20% + Examination (3 hours): 70%
Students are required to achieve at least 45% in the total continuous assessment component and at least 45% in the final examination component and an overall mark of 50% to achieve a pass grade in the unit. Students failing to achieve this requirement will be given a maximum of 45% in the unit.
Workload requirements
2 hours of lectures, 3 hours of practice classes and 7 hours week of private study by the student
See also Unit timetable information
Chief examiner(s)
Prerequisites
TRC3300
Prohibitions
ECE4708, ECE5708, GSE4703