Ying Tan
Affiliations:- Taiyuan University of Science and Technology, Department of Computer Science and Technology, China
According to our database1,
Ying Tan
authored at least 38 papers
between 2007 and 2021.
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Bibliography
2021
IEEE Trans. Evol. Comput., 2021
Knowl. Based Syst., 2021
Neighborhood samples and surrogate assisted multi-objective evolutionary algorithm for expensive many-objective optimization problems.
Appl. Soft Comput., 2021
2020
Granularity-based surrogate-assisted particle swarm optimization for high-dimensional expensive optimization.
Knowl. Based Syst., 2020
Truncation-learning-driven surrogate assisted social learning particle swarm optimization for computationally expensive problem.
Appl. Soft Comput., 2020
A Surrogate-Assisted Evolutionary Algorithm with Random Feature Selection for Large-Scale Expensive Problems.
Proceedings of the Parallel Problem Solving from Nature - PPSN XVI, 2020
2019
Multiobjective Infill Criterion Driven Gaussian Process-Assisted Particle Swarm Optimization of High-Dimensional Expensive Problems.
IEEE Trans. Evol. Comput., 2019
A comparison of quality measures for model selection in surrogate-assisted evolutionary algorithm.
Soft Comput., 2019
A generation-based optimal restart strategy for surrogate-assisted social learning particle swarm optimization.
Knowl. Based Syst., 2019
A New Selection Strategy for Decomposition-based Evolutionary Many-Objective Optimization.
Proceedings of the IEEE Congress on Evolutionary Computation, 2019
2018
Adaptive Information Granulation in Fitness Estimation for Evolutionary Optimization.
Wirel. Pers. Commun., 2018
Semi-supervised learning assisted particle swarm optimization of computationally expensive problems.
Proceedings of the Genetic and Evolutionary Computation Conference, 2018
2017
Comparisons of different kernels in Kriging-assisted evolutionary expensive optimization.
Proceedings of the 2017 IEEE Symposium Series on Computational Intelligence, 2017
Clustering-based evolution control for surrogate-assisted particle swarm optimization.
Proceedings of the 2017 IEEE Congress on Evolutionary Computation, 2017
2013
The selection strategy of mass functions in artificial physics optimisation algorithm.
Int. J. Model. Identif. Control., 2013
Int. J. Comput. Appl. Technol., 2013
Mass functions design of artificial physics optimisation algorithm for constrained optimisation problem.
Int. J. Comput. Appl. Technol., 2013
2012
Int. J. Bio Inspired Comput., 2012
2011
J. Comput., 2011
Hybrid group search optimiser with quadratic interpolation method and its application.
Int. J. Wirel. Mob. Comput., 2011
Int. J. Model. Identif. Control., 2011
Int. J. Intell. Inf. Database Syst., 2011
Particle swarm optimisation based on self-organisation topology driven by different fitness rank.
Int. J. Comput. Sci. Eng., 2011
A study on the effect of Vmax in Artificial physics optimization algorithm with high dimension.
Proceedings of the Third International Conference of Soft Computing and Pattern Recognition, 2011
Proceedings of the 10th IEEE International Conference on Cognitive Informatics and Cognitive Computing, 2011
2010
An Artificial Physics Optimization Algorithm for Multi-Objective Problems Based on Virtual Force Sorting Proceedings.
Proceedings of the Swarm, Evolutionary, and Memetic Computing, 2010
Proceedings of the International Conference on Computational Aspects of Social Networks, 2010
Proceedings of the International Conference on Computational Aspects of Social Networks, 2010
Proceedings of the International Conference on Computational Aspects of Social Networks, 2010
2009
A study on the effect of v<sub>max</sub> in particle swarm optimisation with high dimension.
Int. J. Bio Inspired Comput., 2009
Int. J. Bio Inspired Comput., 2009
2008
2007
Proceedings of the Bio-Inspired Computational Intelligence and Applications, 2007
Proceedings of the Computational and Ambient Intelligence, 2007
Proceedings of the Advances in Computation and Intelligence, 2007
Proceedings of the Third International Conference on Natural Computation, 2007