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Computational Intelligence: Introduction. Ranga Rodrigo January 27, 2014. Summary of Module Contents.
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Computational Intelligence: Introduction Ranga Rodrigo January 27, 2014
Summary of Module Contents • The module introduces the students to the area of computational intelligence with the emphasis on the design and implementation of such intelligent technologies as neural networks, fuzzy logic and genetic algorithms. This will involve practical implementations through a software approach using the Matlab environment.
Aim • Aim: to introduce final year students to the research domain of computational intelligence and to provide both a theoretical and practical description of how computational intelligence systems are designed and implemented.
Outcomes • LO1 Understand and design a learning system using neural networks. • LO2 Understand and design an optimisation and search system using genetic algorithms. • LO3 Understand the benefits of intelligent techniques in practical applications • LO4 Have a critical awareness of the strengths and weaknesses of the techniques presented in the module.
Topics • Mimicking Nature for Problem Solving: The Basic Concepts • Single-Layer and Multi-Layer Feed forward Neural Networks • Associative Memories • Learning Vector Quantizer (LVQ) • Self-Organizing Feature Maps • Genetic Algorithms • Genetic Programming • Fuzzy Systems • The Power and Computational Complexity of Computational Intelligence Models • Book: P. Engelbrecht, Computational Intelligence: An Introduction, John Wiley & Sons, Ltd., 2002.
Assessment • Coursework (40%, score at least 1/3) • Cw1: A case study issued at the end of week 3 to be completed at week 10 or GIS week. The case studies enable students to investigate the theory presented in the lectures in a practical sense by performing simulations in Matlab. This tests the student’s abilities of deeper understanding and analysis. • Cw2 one hour, open book, multiple choice test, in week 7/8 covering all topics of the first six weeks. Quick feedback helps to identify students' weaknesses and act as a guide for future revision. Full discussion of results and solution sheet given in week 10. This imprints fundamental concepts and provides feedback. • Final examination (60% score at least 1/3