@inproceedings{61e6524ac5144ecdbd4be73a471f2cad,
title = "A framework of an intelligent recommendation system for particle swarm optimization based on meta-learning",
abstract = "Particle swarm optimization has shown great advantages to solve NP-hard problems due to its simplicity, intelligence, efficiency and easy enhancement. However, with a large number of particle swarm optimization variants (PSOs) proposed, there are two issues: First, are the general problems of PSOs in terms of premature convergence, universality and robustness solved thoroughly? Second, how to find the relatively appropriate PSOs in a quick and efficient way when facing real-world complex optimization problems? Therefore, it is so necessary to develop an intelligent recommendation system for PSOs to provide users a black-box tool for various application problems.",
keywords = "Meta-learning, PSOs, Recommendation system",
author = "Liu, \{Xue Min\} and Li Li and Jia Wang and Ge, \{Jiao Ju\} and Jun Wang",
note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 25th Annual International Conference on Management Science and Engineering, ICMSE 2018 ; Conference date: 17-08-2018 Through 20-08-2018",
year = "2018",
month = aug,
doi = "10.1109/ICMSE.2018.8745084",
language = "英语",
series = "International Conference on Management Science and Engineering - Annual Conference Proceedings",
publisher = "IEEE Computer Society",
pages = "507--513",
editor = "Ma Tao and Shao Zhen and Mengyue Li",
booktitle = "2018 International Conference on Management Science and Engineering - 25th Annual Proceedings, ICMSE 2018",
address = "美国",
}