Subject Descriptions - Subject Information

Calendar: 2017 Postgraduate
Faculty: Faculty of Engineering and Information Sciences
Department: School of Computing and Information Technology

Subject Information
Subject Code CSCI964
Subject Name Computational Intelligence
Credit Points 6
Pre-Requisites CSCI924
Co-Requisites nil
Restrictions None.
Equivalence None.
Assessment Exam 60% Assignment 40%
General Subject No.
EFTSL (Non Weighted) 0.125
Non Weighted Student Contribution Amounts
Commonwealth Supported (HECS) Students Only
Pre-1997 Pre-2005 Post-2005 Post-2008 Post-2009 Post-2010
$ 1131  $ 1131  $ 1131  $ 1131  $ 1131  $ 1131 
Weighted Student Contribution Amounts  
Work Experience No
Tutorial Enrolment Information no tutorial for this subject

Subject Availability
Session Autumn  (27-02-2017 to 22-06-2017)
Campus Wollongong
Delivery Method On Campus
Instance Name Class 1
Course Restrictions No restrictions
Contact Hours  
Lecturer(s) and
Cons. times
Lei Wang
Coordinator(s) and
Cons. times
Lei Wang
Instance Comment  
Census Date 31-03-2017

Subject Description
This subject introduces students to the basics of "soft" computing. Primary focus will be on artificial neural networks, with some attention also given to genetic algorithms, (evolutionary computing), fuzzy logic and neurofuzzy expert systems. Several application areas will be discussed, primarily pattern recognition and/or classification.

Subject Learning Outcomes
On successful completion of this subject, students will be able to:
1. Explain the architecture and learning algorithms of the more commonly encountered neural network models.
2. Understand the strengths and limitations of artificial neural networks (ANNs/EAs/Fuzzy).
3. Be able to apply ANNs/EAs/Fuzzy to typical pattern recognition and/or classification problems.
4. Understand the need for preprocessing the available neural data.

Textbook Information

Text book information is available via the UniShop website:

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