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Gramophone Noise Reconstruction - A Comparative Study of Interpolation Algorithms for Noise Reduction., and . SIGMAP, page 31-38. SciTePress, (2015)Key challenges and future directions of dynamic multi-objective optimisation., , and . CEC, page 1256-1261. IEEE, (2016)Saturation in PSO neural network training: Good or evil?, and . CEC, page 125-132. IEEE, (2015)The Effect of Quantum and Charged Particles on the Performance of the Dynamic Vector-evaluated Particle Swarm Optimisation Algorithm., and . GECCO, page 25-32. ACM, (2015)Self-Adapting the Brownian Radius in a Differential Evolution Algorithm for Dynamic Environments., , and . FOGA, page 114-128. ACM, (2015)A generator for dynamically constrained optimization problems., and . GECCO (Companion), page 1441-1448. ACM, (2019)Control parameter sensitivity analysis of the multi-guide particle swarm optimization algorithm., and . GECCO, page 22-29. ACM, (2019)An Analysis of Control Parameter Importance in the Particle Swarm Optimization Algorithm., , and . ICSI (1), volume 11655 of Lecture Notes in Computer Science, page 93-105. Springer, (2019)Computational Intelligence: An Introduction. Wiley, (2002)Image Classification using Particle Swarm Optimization., , and . SEAL, volume 2 of Advances in Natural Computation, page 347-365. World Scientific, (2002)