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Demonstrating the power of object-oriented genetic programming via the inference of graph models for complex networks.

, , and . NaBIC, page 305-311. IEEE, (2014)

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An adaptive particle swarm optimization algorithm based on optimal parameter regions., , and . SSCI, page 1-8. IEEE, (2017)Self-adaptive particle swarm optimization: a review and analysis of convergence., , and . Swarm Intelligence, 12 (3): 187-226 (2018)A parameter-free particle swarm optimization algorithm using performance classifiers., , and . Inf. Sci., (2019)Demonstrating the power of object-oriented genetic programming via the inference of graph models for complex networks., , and . NaBIC, page 305-311. IEEE, (2014)The Effect of Probability Distributions on the Performance of Quantum Particle Swarm Optimization for Solving Dynamic Optimization Problems., , and . SSCI, page 242-250. IEEE, (2015)Visualizing and Characterizing the Parameter Configuration Landscape of Particle Swarm Optimization using Physical Landform Classification., , and . CEC, page 2299-2306. IEEE, (2021)The Parameter Configuration Landscape: A Case Study on Particle Swarm Optimization., , and . CEC, page 808-814. IEEE, (2019)Optimal parameter regions for particle swarm optimization algorithms., , and . CEC, page 349-356. IEEE, (2017)Automatic inference of graph models for directed complex networks using genetic programming., , and . CEC, page 2337-2344. IEEE, (2016)A radius-free quantum particle swarm optimization technique for dynamic optimization problems., , and . CEC, page 578-585. IEEE, (2016)