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Andries P. Engelbrecht
Publications
- 2024
- [j115]Andries P. Engelbrecht, Robert Gouldie:
Fitness Landscape Analysis of Product Unit Neural Networks. Algorithms 17(6): 241 (2024) - [j113]Daniel H. Von Eschwege, Andries P. Engelbrecht:
Belief space-guided approach to self-adaptive particle swarm optimization. Swarm Intell. 18(1): 31-78 (2024) - [c262]Mari Spangenberg, Andries P. Engelbrecht:
Set-Based Particle Swarm Optimization for the Multi-objective Multi-dimensional Knapsack Problem. ICSI (1) 2024: 3-19 - 2023
- [j110]Kyle Erwin, Andries P. Engelbrecht:
Multi-Guide Set-Based Particle Swarm Optimization for Multi-Objective Portfolio Optimization. Algorithms 16(2): 62 (2023) - [j108]Kyle Erwin, Andries P. Engelbrecht:
Feature-Based Complexity Measure for Multinomial Classification Datasets. Entropy 25(7): 1000 (2023) - [j107]Kyle Erwin, Andries P. Engelbrecht:
Meta-heuristics for portfolio optimization. Soft Comput. 27(24): 19045-19073 (2023) - [c259]Lauren Hayward, Andries P. Engelbrecht:
How to Tell a Fish from a Bee: Constructing Meta-Heuristic Search Behaviour Characteristics. GECCO Companion 2023: 1562-1569 - [c257]Rijk Marius de Wet, Andries P. Engelbrecht:
Set-based Particle Swarm Optimization for Data Clustering: Comparison and Analysis of Control Parameters. ISMSI 2023: 103-110 - [c256]Daniel H. Von Eschwege, Andries P. Engelbrecht:
A Cautionary Note on Poli's Stability Condition for Particle Swarm Optimization. SSCI 2023: 1189-1194 - [c255]Kyle Erwin, Andries P. Engelbrecht:
Meta-heuristics for Portfolio Optimization: Part I - Review of Meta-heuristics. ICSI (2) 2023: 441-452 - [c254]Kyle Erwin, Andries P. Engelbrecht:
Meta-heuristics for Portfolio Optimization: Part II - Empirical Analysis. ICSI (2) 2023: 453-464 - 2022
- [c252]Weka Steyn, Andries P. Engelbrecht:
Dynamic Spatial Guided Multi-Guide Particle Swarm Optimization Algorithm for Many-Objective Optimization. ANTS Conference 2022: 130-141 - [c249]Jean-Pierre van Zyl, Andries P. Engelbrecht:
Rule Induction Using Set-Based Particle Swarm Optimisation. CEC 2022: 1-8 - [c247]Lienke Brown, Andries P. Engelbrecht:
Set-based Particle Swarm Optimization for Data Clustering. ISMSI 2022: 43-49 - [c246]Weka Steyn, Andries P. Engelbrecht:
Stability-Guided Multi-Guide Particle Swarm Optimization. ISMSI 2022: 55-61 - [c245]Donovan Edeling, Andries P. Engelbrecht:
Static Polynomial Approximation Using Set-based Particle Swarm Optimisation. ISMSI 2022: 67-72 - [c242]Kyle Erwin, Andries P. Engelbrecht:
Improved Hamming Diversity Measure for Set-Based Optimization Algorithms. ICSI (1) 2022: 39-47 - 2021
- [j98]Salihu A. Abdulkarim, Andries P. Engelbrecht:
Time series forecasting with feedforward neural networks trained using particle swarm optimizers for dynamic environments. Neural Comput. Appl. 33(7): 2667-2683 (2021) - [j96]Cian Steenkamp, Andries P. Engelbrecht:
A scalability study of the multi-guide particle swarm optimization algorithm to many-objectives. Swarm Evol. Comput. 66: 100943 (2021) - [c237]James Faure, Andries P. Engelbrecht:
A Convolutional Neural Network for Dental Panoramic Radiograph Classification. ISMSI 2021: 54-59 - [c236]Stefan van Deventer, Andries P. Engelbrecht:
Learning to Trade from Zero-Knowledge Using Particle Swarm Optimization. IWANN (2) 2021: 183-195 - [c235]James Faure, Andries P. Engelbrecht:
Impacted Tooth Detection in Panoramic Radiographs. IWANN (1) 2021: 525-536 - [c234]Kyle Erwin, Andries P. Engelbrecht:
Set-based Particle Swarm Optimization for Portfolio Optimization with Adaptive Coordinate Descent Weight Optimization. SSCI 2021: 1-8 - [c233]Kyle Erwin, Andries P. Engelbrecht:
A Tuning Free Approach to Multi-guide Particle Swarm Optimization. SSCI 2021: 1-8 - [c232]Timothy G. Carolus, Andries P. Engelbrecht:
Multi-guide Particle Swarm Optimisation Control Parameter Importance in High Dimensional Spaces. ICSI (1) 2021: 185-198 - [c231]Jean-Pierre van Zyl, Andries P. Engelbrecht:
Polynomial Approximation Using Set-Based Particle Swarm Optimization. ICSI (1) 2021: 210-222 - 2020
- [c229]Timothy G. Carolus, Andries P. Engelbrecht:
Control Parameter Importance and Sensitivity Analysis of the Multi-Guide Particle Swarm Optimization Algorithm. ANTS Conference 2020: 96-106 - [c228]Heinrich Cilliers, Andries P. Engelbrecht:
Fitting Gaussian Mixture Models Using Cooperative Particle Swarm Optimization. ANTS Conference 2020: 298-305 - [c227]Kyle Erwin, Andries P. Engelbrecht:
Set-Based Particle Swarm Optimization for Portfolio Optimization. ANTS Conference 2020: 333-339 - [c226]Simon Dennis, Andries P. Engelbrecht:
A Review and Empirical Analysis of Particle Swarm optimization Algorithms for Dynamic Multi-Modal optimization. CEC 2020: 1-8 - [c220]Callum Parton, Andries P. Engelbrecht:
Mixtures of Heterogeneous Experts. ISMSI 2020: 1-7 - [c216]Simon Dennis, Andries P. Engelbrecht:
Dynamic Multi-Swarm Fractional-best Particle Swarm Optimization for Dynamic Multi-modal Optimization. SSCI 2020: 1549-1556 - [c215]Thorsten Schmidt-Dumont, Andries P. Engelbrecht:
Analysis of Particle Swarm Optimisation for Training Support Vector Machines. SSCI 2020: 1557-1564 - [c214]Kyle Erwin, Andries P. Engelbrecht:
Improved Set-based Particle Swarm optimization for Portfolio optimization. SSCI 2020: 1573-1580 - 2019
- [j84]Salihu A. Abdulkarim, Andries P. Engelbrecht:
Time Series Forecasting Using Neural Networks: Are Recurrent Connections Necessary? Neural Process. Lett. 50(3): 2763-2795 (2019) - [c210]Kyle Erwin, Andries P. Engelbrecht:
Control parameter sensitivity analysis of the multi-guide particle swarm optimization algorithm. GECCO 2019: 22-29 - 2017
- [j73]Christoph F. Stallmann, Andries P. Engelbrecht:
Gramophone Noise Detection and Reconstruction Using Time Delay Artificial Neural Networks. IEEE Trans. Syst. Man Cybern. Syst. 47(6): 893-905 (2017) - [c192]Jaco Cronje, Andries P. Engelbrecht:
Training Convolutional Neural Networks with Class Based Data Augmentation for Detecting Distracted Drivers. ICCAE 2017: 126-130 - 2016
- [c178]E. T. van Zyl, Andries P. Engelbrecht:
Group-based stochastic scaling for PSO velocities. CEC 2016: 1862-1868 - [c166]Albert Volschenk, Andries P. Engelbrecht:
An Analysis of Competitive Coevolutionary Particle Swarm Optimizers to Train Neural Network Game Tree Evaluation Functions. ICSI (1) 2016: 369-380 - 2015
- [c154]Christoph F. Stallmann, Andries P. Engelbrecht:
Signal Modelling for the Digital Reconstruction of Gramophone Noise. ICETE (Selected Papers) 2015: 411-432 - [c152]Christoph F. Stallmann, Andries P. Engelbrecht:
Gramophone Noise Reconstruction - A Comparative Study of Interpolation Algorithms for Noise Reduction. SIGMAP 2015: 31-38 - [c151]Elre Van Zyl, Andries P. Engelbrecht:
A Subspace-Based Method for PSO Initialization. SSCI 2015: 226-233 - 2014
- [c138]Jade Z. Abbott, Andries P. Engelbrecht:
Nature-Inspired Swarm Robotics Algorithms for Prioritized Foraging. ANTS Conference 2014: 246-253 - [c137]Kristina S. Georgieva, Andries P. Engelbrecht:
Cooperative DynDE for temporal data clustering. IEEE Congress on Evolutionary Computation 2014: 437-444 - [c135]Robert W. Garden, Andries P. Engelbrecht:
Analysis and classification of optimisation benchmark functions and benchmark suites. IEEE Congress on Evolutionary Computation 2014: 1641-1649 - [c130]Ronald Klazar, Andries P. Engelbrecht:
Parameter optimization by means of statistical quality guides in F-Race. IEEE Congress on Evolutionary Computation 2014: 2547-2552 - [c122]E. T. van Zyl, Andries P. Engelbrecht:
Comparison of self-adaptive particle swarm optimizers. SIS 2014: 48-56 - 2013
- [j57]Mario Poggiolini, Andries P. Engelbrecht:
Application of the feature-detection rule to the Negative Selection Algorithm. Expert Syst. Appl. 40(8): 3001-3014 (2013) - [j56]Patricia E. N. Lutu, Andries P. Engelbrecht:
Base Model Combination Algorithm for Resolving Tied Predictions for K-Nearest Neighbor OVA Ensemble Models. INFORMS J. Comput. 25(3): 517-526 (2013) - [j55]Patricia E. N. Lutu, Andries P. Engelbrecht:
Positive-versus-Negative Classification for Model Aggregation in Predictive Data Mining. INFORMS J. Comput. 25(4): 792-807 (2013) - [c110]Kristina Georgieva, Andries P. Engelbrecht:
A cooperative multi-population approach to clustering temporal data. IEEE Congress on Evolutionary Computation 2013: 1983-1991 - [c104]Kristina Georgieva, Andries P. Engelbrecht:
Dynamic Differential Evolution Algorithm for Clustering Temporal Data. LSSC 2013: 240-247 - 2012
- [j48]Patricia E. N. Lutu, Andries P. Engelbrecht:
Using OVA modeling to improve classification performance for large datasets. Expert Syst. Appl. 39(4): 4358-4376 (2012) - [j46]A. J. Graaff, Andries P. Engelbrecht:
Clustering data in stationary environments with a local network neighborhood artificial immune system. Int. J. Mach. Learn. Cybern. 3(1): 1-26 (2012) - [c100]Adiel Ismail, Andries P. Engelbrecht:
Measuring Diversity in the Cooperative Particle Swarm Optimizer. ANTS 2012: 97-108 - [c98]Adiel Ismail, Andries P. Engelbrecht:
The Self-adaptive Comprehensive Learning Particle Swarm Optimizer. ANTS 2012: 156-167 - [c96]Ronald Klazar, Andries P. Engelbrecht:
Dynamic Load Balancing Inspired by Cemetery Formation in Ant Colonies. ANTS 2012: 236-243 - [c95]Jade Z. Abbott, Andries P. Engelbrecht:
Performance of Bacterial Foraging Optimization in Dynamic Environments. ANTS 2012: 284-291 - [c93]Julien G. O. L. Duhain, Andries P. Engelbrecht:
Towards a more complete classification system for dynamically changing environments. IEEE Congress on Evolutionary Computation 2012: 1-8 - [c89]Adiel Ismail, Andries P. Engelbrecht:
Self-Adaptive Particle Swarm Optimization. SEAL 2012: 228-237 - 2011
- [j42]A. J. Graaff, Andries P. Engelbrecht:
Using sequential deviation to dynamically determine the number of clusters found by a local network neighbourhood artificial immune system. Appl. Soft Comput. 11(2): 2698-2713 (2011) - [j41]A. L. Louis, Andries P. Engelbrecht:
Unsupervised discovery of relations for analysis of textual data. Digit. Investig. 7(3-4): 154-171 (2011) - [j40]A. J. Graaff, Andries P. Engelbrecht:
Clustering data in an uncertain environment using an artificial immune system. Pattern Recognit. Lett. 32(2): 342-351 (2011) - [c75]Ronald Klazar, Andries P. Engelbrecht:
Dynamic load balancing inspired by division of labour in ant colonies. SWIS 2011: 184-191 - 2010
- [j37]Patricia E. N. Lutu, Andries P. Engelbrecht:
A decision rule-based method for feature selection in predictive data mining. Expert Syst. Appl. 37(1): 602-609 (2010) - [j35]Isabella Lona Schoeman, Andries P. Engelbrecht:
A novel particle swarm niching technique based on extensive vector operations. Nat. Comput. 9(3): 683-701 (2010) - [c73]Isabella Schoeman, Andries P. Engelbrecht:
Effect of Particle Initialization on the Performance of Particle Swarm Niching Algorithms. ANTS Conference 2010: 560-561 - 2009
- [c64]Olusegun Olorunda, Andries P. Engelbrecht:
An analysis of heterogeneous cooperative algorithms. IEEE Congress on Evolutionary Computation 2009: 1562-1569 - [c62]Isabella Lona Schoeman, Andries P. Engelbrecht:
Scalability of the vector-based Particle Swarm Optimizer. IEEE Congress on Evolutionary Computation 2009: 1995-2001 - 2008
- [j30]Gavin Potgieter, Andries P. Engelbrecht:
Evolving model trees for mining data sets with continuous-valued classes. Expert Syst. Appl. 35(4): 1513-1532 (2008) - [j29]Daniel Rodic, Andries P. Engelbrecht:
Social networks in simulated multi-robot environment. Int. J. Intell. Comput. Cybern. 1(1): 110-127 (2008) - [c55]A. J. Graaff, Andries P. Engelbrecht:
Towards a self regulating local network neighbourhood artificial immune system for data clustering. IEEE Congress on Evolutionary Computation 2008: 633-640 - [c52]Olusegun Olorunda, Andries P. Engelbrecht:
Measuring exploration/exploitation in particle swarms using swarm diversity. IEEE Congress on Evolutionary Computation 2008: 1128-1134 - 2007
- [j27]Gavin Potgieter, Andries P. Engelbrecht:
Genetic algorithms for the structural optimisation of learned polynomial expressions. Appl. Math. Comput. 186(2): 1441-1466 (2007) - [j25]Patricia E. N. Lutu, Andries P. Engelbrecht:
A Comparative study of sample selection methods for classification. ARIMA J. 6: 6 (2007) - [j23]Ulrich Paquet, Andries P. Engelbrecht:
Particle Swarms for Linearly Constrained Optimisation. Fundam. Informaticae 76(1-2): 147-170 (2007) - [c44]A. J. Graaff, Andries P. Engelbrecht:
A local network neighbourhood artificial immune system for data clustering. IEEE Congress on Evolutionary Computation 2007: 260-267 - [c43]Olusegun Olorunda, Andries P. Engelbrecht:
Differential evolution in high-dimensional search spaces. IEEE Congress on Evolutionary Computation 2007: 1934-1941 - [c40]Andries P. Engelbrecht, L. N. H. van Loggerenberg:
Enhancing the NichePSO. IEEE Congress on Evolutionary Computation 2007: 2297-2302 - [c38]Willem H. Duminy, Andries P. Engelbrecht:
Tournament Particle Swarm Optimization. CIG 2007: 146-153 - 2006
- [j18]Patricia E. N. Lutu, Andries P. Engelbrecht:
A comparative study of sample selection methods for classification. South Afr. Comput. J. 36: 69-85 (2006) - [c32]Marais Neethling, Andries P. Engelbrecht:
Determining RNA Secondary Structure using Set-based Particle Swarm Optimization. IEEE Congress on Evolutionary Computation 2006: 1670-1677 - [c30]Johan Conradie, Andries P. Engelbrecht:
Training Bao Game-Playing Agents using Coevolutionary Particle Swarm Optimization. CIG 2006: 67-74 - [c28]Isabella Schoeman, Andries P. Engelbrecht:
Niching for Dynamic Environments Using Particle Swarm Optimization. SEAL 2006: 134-141 - 2005
- [j14]Willem H. Duminy, Andries P. Engelbrecht:
Composing linear evaluation functions from observable features. South Afr. Comput. J. 35: 48-58 (2005) - 2004
- [j11]Daniel Rodic, Andries P. Engelbrecht:
Social networks as a task allocation tool for multi-robot teams. South Afr. Comput. J. 33: 52-66 (2004) - [j9]L. Messerschmidt, Andries P. Engelbrecht:
Learning to Play Games Using a PSO-Based Competitive Learning Approach. IEEE Trans. Evol. Comput. 8(3): 280-288 (2004) - 2003
- [c18]D. W. van der Merwe, Andries P. Engelbrecht:
Data clustering using particle swarm optimization. IEEE Congress on Evolutionary Computation 2003: 215-220 - [c17]Ulrich Paquet, Andries P. Engelbrecht:
A new particle swarm optimiser for linearly constrained optimisation. IEEE Congress on Evolutionary Computation 2003: 227-233 - 2000
- [c10]S. E. Rouwhorst, Andries P. Engelbrecht:
Searching the forest: using decision trees as building blocks for evolutionary search in classification databases. CEC 2000: 633-638 - [c9]Adiel Ismail, Andries P. Engelbrecht:
Global Optimization Algorithms for Training Product Unit Neural Networks. IJCNN (1) 2000: 132-137 - 1999
- [c8]E. Basson, Andries P. Engelbrecht:
Approximation of a function and its derivatives in feedforward neural networks. IJCNN 1999: 419-421
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