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https://doi.org/10.1080/00051144.2018.1465680

New intelligent optimization framework

As Xie ; China Institute for SMEs, Zhejiang University of Technology, Hangzhou, People’s Republic of China

Puni tekst: engleski, pdf (3 MB) str. 231-253 preuzimanja: 96* citiraj
APA 6th Edition
Xie, A. (2018). New intelligent optimization framework. Automatika, 59 (2), 231-253. https://doi.org/10.1080/00051144.2018.1465680
MLA 8th Edition
Xie, As. "New intelligent optimization framework." Automatika, vol. 59, br. 2, 2018, str. 231-253. https://doi.org/10.1080/00051144.2018.1465680. Citirano 10.07.2020.
Chicago 17th Edition
Xie, As. "New intelligent optimization framework." Automatika 59, br. 2 (2018): 231-253. https://doi.org/10.1080/00051144.2018.1465680
Harvard
Xie, A. (2018). 'New intelligent optimization framework', Automatika, 59(2), str. 231-253. https://doi.org/10.1080/00051144.2018.1465680
Vancouver
Xie A. New intelligent optimization framework. Automatika [Internet]. 2018 [pristupljeno 10.07.2020.];59(2):231-253. https://doi.org/10.1080/00051144.2018.1465680
IEEE
A. Xie, "New intelligent optimization framework", Automatika, vol.59, br. 2, str. 231-253, 2018. [Online]. https://doi.org/10.1080/00051144.2018.1465680

Sažetak
Generally, the “intelligence” of the intelligent optimization algorithms is mainly dependent on the probability and operational rules. Thus there are always some probability equations or mathematical formulations that need to be updated. This paper proposes an algorithm model that
needs no probability tuning. The algorithm designed according to the guiding principles and specific methods of benchmarking proposed in this paper is able to achieve the synergistic coexistence and automatic balance of exploration and exploitation, thus the population diversity
will be kept during the running. The algorithm model proposed here is between engineering technology and cognitive philosophy, it is not just a specific algorithm, but a kind of general methodology and/or a mode of thinking. The successful application of some realistic issues, like
distributed power generation optimization configuration, verified its applicability.

Ključne riječi
Intelligent optimization; optimization algorithm; meta-heuristic method; encoding scheme; benchmarking philosophy

Hrčak ID: 225198

URI
https://hrcak.srce.hr/225198

Posjeta: 160 *