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Marde Helbig (Greeff)
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Cited by
Cited by
Year
Performance measures for dynamic multi-objective optimisation algorithms
M Helbig, AP Engelbrecht
Information Sciences 250, 61-81, 2013
1232013
Solving dynamic multi-objective problems with vector evaluated particle swarm optimisation
M Greeff, AP Engelbrecht
2008 IEEE Congress on Evolutionary Computation (IEEE World Congress on …, 2008
1132008
Visualising basins of attraction for the cross-entropy and the squared error neural network loss functions
AS Bosman, A Engelbrecht, M Helbig
Neurocomputing 400, 113-136, 2020
852020
Benchmarks for dynamic multi-objective optimisation algorithms
M Helbig, AP Engelbrecht
ACM Computing Surveys (CSUR) 46 (3), 1-39, 2014
822014
Analysing the performance of dynamic multi-objective optimisation algorithms
M Helbig, AP Engelbrecht
2013 IEEE Congress on Evolutionary Computation, 1531-1539, 2013
592013
Population-based metaheuristics for continuous boundary-constrained dynamic multi-objective optimisation problems
M Helbig, AP Engelbrecht
Swarm and Evolutionary computation 14, 31-47, 2014
582014
Dynamic Multi-Objective Optimization Using PSO
M Helbig, A Engelbrecht
Metaheuristics for Dynamic Optimization, 147-188, 2013
522013
Archive management for dynamic multi-objective optimisation problems using vector evaluated particle swarm optimisation
M Helbig, AP Engelbrecht
2011 IEEE Congress of Evolutionary Computation (CEC), 2047-2054, 2011
512011
Benchmarks for dynamic multi-objective optimisation
M Helbig, AP Engelbrecht
2013 IEEE Symposium on Computational Intelligence in Dynamic and Uncertain …, 2013
492013
Dynamic multi-objective optimisation using PSO
M Greeff, AP Engelbrecht
Multi-Objective Swarm Intelligent Systems: Theory & Experiences, 105-123, 2010
442010
Benchmark functions for cec 2015 special session and competition on dynamic multi-objective optimization
M Helbig, A Engelbrecht
Dept. Comput. Sci., Univ. Pretoria, Pretoria, South Africa, Rep, 2015
402015
Solving dynamic multi-objective optimisation problems using vector evaluated particle swarm optimisation
M Helbig
University of Pretoria, 2012
342012
Analyses of guide update approaches for vector evaluated particle swarm optimisation on dynamic multi-objective optimisation problems
M Helbig, AP Engelbrecht
2012 IEEE Congress on Evolutionary Computation, 1-8, 2012
342012
Heterogeneous dynamic vector evaluated particle swarm optimisation for dynamic multi-objective optimisation
M Helbig, AP Engelbrecht
2014 IEEE Congress on Evolutionary Computation (CEC), 3151-3159, 2014
302014
Interactive cultural experiences using virtual identities
M Greeff, V Lalioti
272001
Key challenges and future directions of dynamic multi-objective optimisation
M Helbig, K Deb, A Engelbrecht
2016 IEEE Congress on Evolutionary Computation (CEC), 1256-1261, 2016
232016
Fitness landscape analysis of weight-elimination neural networks
A Bosman, A Engelbrecht, M Helbig
Neural Processing Letters 48, 353-373, 2018
192018
A lightweight methodology to improve web accessibility
M Greeff, P Kotzé
Proceedings of the 2009 Annual Research Conference of the South African …, 2009
172009
Progressive gradient walk for neural network fitness landscape analysis
AS Bosman, AP Engelbrecht, M Helbig
Proceedings of the Genetic and Evolutionary Computation Conference Companion …, 2018
162018
Search space boundaries in neural network error landscape analysis
AS Bosman, A Engelbrecht, M Helbig
2016 IEEE Symposium Series on Computational Intelligence (SSCI), 1-8, 2016
152016
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Articles 1–20