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Key challenges and future directions of dynamic multi-objective optimisation., , и . CEC, стр. 1256-1261. IEEE, (2016)Gramophone Noise Reconstruction - A Comparative Study of Interpolation Algorithms for Noise Reduction., и . SIGMAP, стр. 31-38. SciTePress, (2015)Saturation in PSO neural network training: Good or evil?, и . CEC, стр. 125-132. IEEE, (2015)Self-Adapting the Brownian Radius in a Differential Evolution Algorithm for Dynamic Environments., , и . FOGA, стр. 114-128. ACM, (2015)Optimal parameter regions and the time-dependence of control parameter values for the particle swarm optimization algorithm., , и . Swarm Evol. Comput., (2018)A Scalability Study of Many-Objective Optimization Algorithms., , и . IEEE Trans. Evol. Comput., 22 (1): 79-96 (2018)Particle swarm optimization approaches to coevolve strategies for the iterated prisoner's dilemma., и . IEEE Trans. Evol. Comput., 9 (6): 562-579 (2005)Positive-versus-Negative Classification for Model Aggregation in Predictive Data Mining., и . INFORMS J. Comput., 25 (4): 792-807 (2013)Gramophone Noise Detection and Reconstruction Using Time Delay Artificial Neural Networks., и . IEEE Trans. Syst. Man Cybern. Syst., 47 (6): 893-905 (2017)Control parameter sensitivity analysis of the multi-guide particle swarm optimization algorithm., и . GECCO, стр. 22-29. ACM, (2019)