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PUBLISHED BOOK CHAPTERS


A Building Block Approach to Genetic Programming for Rule Discovery
Engelbrecht, AP. Rouwhorst, S. Schoeman, L. 2001.
in Data Mining: A Heuristic Approach, HA Abbass, R Sarkar, C Newton (eds), Chapter IX, pp 175-189, Idea Group Publishing

Download this publication from the Data Mining group.

Abstract:

This chapter presents a building-block approach to evolving compact decision trees using genetic programming. The algorithm extracts crisp and accurate rules sets, in comparison with C4.5 and CN2.

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Image Classification using Particle Swarm Optimization
Omran, M. Salman, A. Engelbrecht, AP. 2002.
4th Asia-Pacific Conference on Simulated Evolution and Learning

Download this publication from the Swarm Intelligence and Image Analysis groups.

Abstract:

A new image classification algorithm that is based on the particle swarm optimizer (PSO) is proposed in this paper. The algorithm finds the centroids of a user specified number of clusters, where each cluster groups together similar pixels. The new image classifier has been applied successfully to three types of images to illustrate its wide applicability. These images include synthesized, MRI and satellite images. The proposed algorithm is compared with the benchmark classification algorithm, ISODATA, yielding promising results.

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Particle Swarm Optimization for Pattern Recognition and Image Processing
Omran, M. Engelbrecht, AP. Salman, A. 2006.
Swarm Intelligence and Data Mining, A. Abraham, C. Grosan and V. Ramos (Editors), Springer-Verlag, SCI series 'Studies in Computational Intelligence'

Not Available For Download.

Abstract:

Not Available

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Dynamic Multi-Objective Optimisation using PSO
Greef, M. Engelbrecht, AP. 2009.
Multi-Objective Swarm Intelligent Systems, Studies in Computational Intelligence, Springer-Verlag

Not Available For Download.

Abstract:

Not Available

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