Browsing Engineering, Built Environment and Information Technology by UP Author "Engelbrecht, Andries P."

Browsing Engineering, Built Environment and Information Technology by UP Author "Engelbrecht, Andries P."

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  • Application of the feature-detection rule to the negative selection algorithm 
    Poggiolini, Mario; Engelbrecht, Andries P. (Elsevier, 2013-08)
    The Negative Selection Algorithm developed by Forrest et al. was inspired by the way in which T-cell lymphocytes mature within the thymus before being released into the blood system. The mature T-cell lymphocytes exhibit ...
  • Bare bones differential evolution 
    Omran, Mahamed G.H.; Engelbrecht, Andries P.; Salman, Ayed (Elsevier, 2008-07)
    The barebones differential evolution (BBDE) is a new, almost parameter-free optimization algorithm that is a hybrid of the barebones particle swarm optimizer and differential evolution. Differential evolution is used to ...
  • Benchmarks for dynamic multi-objective optimisation algorithms 
    Helbig, Marde; Engelbrecht, Andries P. (Association for Computing, 2014-01)
    Algorithms that solve Dynamic Multi-Objective Optimisation Problems (DMOOPs) should be tested on benchmark functions to determine whether the algorithm can overcome specific difficulties that can occur in real-world problems. ...
  • Boundary constraint handling techniques for particle swarm optimization in high dimensional problem spaces 
    Oldewage, E.T. (Elre); Engelbrecht, Andries P.; Cleghorn, Christopher Wesley (Springer, 2018-10)
    This paper investigates the use of boundary constraint handling mechanisms to prevent unwanted particle roaming behaviour in high dimensional spaces. The paper tests a range of strategies on a benchmark for large scale ...
  • Characterising the searchability of continuous optimisation problems for PSO 
    Malan, Katherine Mary; Engelbrecht, Andries P. (Springer, 2014-12)
    The focus of research in swarm intelligence has been largely on the algorithmic side with relatively little attention being paid to the study of problems and the behaviour of algorithms in relation to problems. When a ...
  • Clustering data in stationary environments with a local network neighborhood artificial immune system 
    Graaff, A.J. (Alexander Jakobus); Engelbrecht, Andries P. (Springer, 2012-03)
    The network theory in immunology inspired the modelling of network based artificial immune system (AIS) models for data clustering. Current network based AIS models determine the network connectivity between artificial ...
  • A comparative study of sample selection methods for classification 
    Lutu, Patricia Elizabeth Nalwoga; Engelbrecht, Andries P. (Computer Society of South Africa, 2006-06)
    Sampling of large datasets for data mining is important for at least two reasons. The processing of large amounts of data results in increased computational complexity. The cost of this additional complexity may not be ...
  • Congestion control in wireless sensor networks based on bird flocking behavior 
    Antoniou, Pavlos; Pitsillides, Andreas; Blackwell, Tim; Engelbrecht, Andries P.; Michael, Loizos (Elsevier, 2013)
    This paper proposes that the flocking behavior of birds can guide the design of a robust, scalable and self-adaptive congestion control protocol in the context of wireless sensor networks (WSNs). The proposed approach ...
  • A convergence proof for the particle swarm optimiser 
    Van den Bergh, Frans; Engelbrecht, Andries P. (IOS Pres, 2010)
    The Particle Swarm Optimiser (PSO) is a population based stochastic optimisation algorithm, empirically shown to be efficient and robust. This paper provides a proof to show that the original PSO does not have guaranteed ...
  • Critical considerations on angle modulated particle swarm optimisers 
    Leonard, Barend J.; Engelbrecht, Andries P.; Cleghorn, Christopher Wesley (Springer, 2015-12)
    This article investigates various aspects of angle modulated particle swarm optimisers (AMPSO). Previous attempts at improving the algorithm have only been able to produce better results in a handful of test cases. With ...
  • Differential evolution for dynamic environments with unknown numbers of optima 
    Du Plessis, M.C. (Mathys Cornelius); Engelbrecht, Andries P. (Springer, 2013-01)
    This paper investigates optimization in dynamic environments where the numbers of optima are unknown or fluctuating. The authors present a novel algorithm, Dynamic Population DifferentialEvolution (DynPopDE),which is ...
  • Diversity rate of change measurement for particle swarm optimisers 
    Bosman, Phlippie; Engelbrecht, Andries P. (Springer, 2014)
    The diversity of a particle swarm can reflect the swarm's explorative/exploitative behaviour at a given time step. This paper pro- poses a diversity rate of change measure to quantify the rate at which particle swarms ...
  • DNA sequence design for DNA computation based on binary particle swarm optimization 
    Ibrahim, Zuwairie; Khalid, Noor Khafifah; Buyamin, Salinda; Ibrahim, Ismail; Mukred, Jameel Abdulla Ahmed; Yusof, Zulkifli Md.; Mohamad, Mohd Saberi; Mokhtar, N.; Saaid, Muhammad Faiz Mohamed; Engelbrecht, Andries P. (ICIC International, 2012-05)
    Deoxyribonucleic Acid (DNA) has certain unique properties such as self- assembly and self-complementary in hybridization, which are important in many DNA- based technologies. DNA computing, for example, uses these ...
  • Fitness landscape analysis of weight-elimination neural networks 
    Bosman, Anna Sergeevna; Engelbrecht, Andries P.; Helbig, Marde (Springer, 2018-08)
    Neural network architectures can be regularised by adding a penalty term to the objective function, thus minimising network complexity in addition to the error. However, adding a term to the objective function inevitably ...
  • A fuzzy particle swarm optimization algorithm for computer communication network topology design 
    Khan, Salman Ahmad; Engelbrecht, Andries P. (Springer, 2011)
    Particle swarm optimization (PSO) is a powerful optimization technique that has been applied to solve a number of complex optimization problems. One such optimization problem is topology design of distributed local area ...
  • Fuzzy particle swarm optimization algorithms for the open shortest path first weight setting problem 
    Mohiuddin, Mohammad A.; Khan, Salman Ahmad; Engelbrecht, Andries P. (Springer, 2016-10)
    The open shortest path first (OSPF) routing protocol is a well-known approach for routing packets from a source node to a destination node. The protocol assigns weights (or costs) to the links of a network. These ...
  • Gaussian-valued particle swarm optimization 
    Harrison, Kyle Robert; Ombuki-Berman, Beatrice M.; Engelbrecht, Andries P. (Springer, 2018-10)
    This paper examines the position update equation of the particle swarm optimization (PSO) algorithm, leading to the proposal of a simplified position update based upon a Gaussian distribution. The proposed algorithm, ...
  • A generalized theoretical deterministic particle swarm model 
    Cleghorn, Christopher Wesley; Engelbrecht, Andries P. (Springer, 2014-03)
    A number of theoretical studies of particle swarm optimization (PSO) have been done to gain a better understanding of the dynamics of the algorithm and the behavior of the particles under different conditions. These ...
  • Gramophone noise detection and reconstruction using time delay artificial neural networks 
    Stallmann, Christoph F.; Engelbrecht, Andries P. (Institute of Electrical and Electronics Engineers, 2017-06)
    Gramophone records were the main recording medium for more than seven decades and regained widespread popularity over the past several years. Being an analog storage medium, gramophone records are subject to distortions ...
  • The importance of component-wise stochasticity in particle swarm optimization 
    Oldewage, E.T. (Elre); Engelbrecht, Andries P.; Cleghorn, Christopher Wesley (Springer, 2018-10)
    This paper illustrates the importance of independent, component-wise stochastic scaling values, from both a theoretical and empirical perspective. It is shown that a swarm employing scalar stochasticity is unable to express ...