Book Chapters¶
2001¶
[1] A. Engelbrecht, S. Rouwhorst, and L. Schoeman, “A building block approach to genetic programming for rule discovery,” in Data mining: A heuristic approach, H. Abbass, R. Sarkar, and C. Newton, Eds. Idea Group Publishing, 2001, pp. 174–189, DOI:https://10.4018/978-1-930708-25-9.ch009.
[2] M. Omran, A. Engelbrecht, and A. Salman, “Image classification using particle swarm optimization,” in Recent advances in simulated evolution and learning, advances in natural computation, vol. 2, K. Tan, M. Lim, X. Yao, and L. Wang, Eds. World Scientific, 2001, pp. 347–365, DOI:https://doi.org/10.1142/9789812561794_0019.
2006¶
[3] M. Omran, A. Engelbrecht, and A. Salman, “Particle swarm optimization for pattern recognition and image processing,” in Swarm intillegence and data mining, vol. 34, A. Abraham, C. Grosan, and V. Ramo, Eds. Springer-Verlag, 2006, pp. 125–151, DOI:https://doi.org/10.1007/978-3-540-34956-3_6.
2013¶
[4] M. du Plessis and A. Engelbrecht, “Self-adapting differential evolution for dynamic environments with fluctuating numbers of optima,” in Metaheuristics for dynamic optimization, vol. 433, Springer-Verlag, 2013, pp. 117–145.
[5] M. Helbig and A. Engelbrecht, “Dynamic multi-objective optimization using pso,” in Metaheuristics for dynamic optimization, vol. 433, Springer-Verlag, 2013, pp. 147–188, DOI:https://doi.org/10.1007/978-3-642-30665-5_8.
2014¶
[6] K. Malan and A. Engelbrecht, “Fitness landscape analysis for metaheuristc performance prediction,” in Recent advances in the theory and application of fitness landscapes, vol. 6, Springer-Verlag, 2014, pp. 103–132, DOI:https://doi.org/10.1007/978-3-642-41888-4_4.
[7] C. Stallmann and A. Engelbrecht, “Signal modelling for the digital reconstruction of gramophone noise,” in Communications in computer and information science, vol. 7899, 2014.