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https://doi.org/10.17559/TV-20170413135109

Improving the Diversity of PSO for an Engineering Inverse Problem using Adaptive Inertia Weight

Shafi Ullah Khan   ORCID icon orcid.org/0000-0002-5706-721X ; Department of Electronics Islamia College University, Peshawar, Pakistan
Obaid Ur Rehman   ORCID icon orcid.org/0000-0003-4577-6059 ; Sarhad University of Science & Information Technology, Peshawar, Pakistan
Naeem Khan   ORCID icon orcid.org/0000-0002-7169-6733 ; Depertment of Electrical Engineering, University of Engineering & Technology, Bannu Campus, Pakistan
Asfandyar Khan ; Department of CS/IT University of Agriculture, Peshawar, Pakistan
Syed Anayat Ali Shah ; Department of Mathimatics, Islamia College University, Peshawar, Pakistan
Shiyou Yang ; College Electrical Engineering, Zhejiang University, Hangzhou, China

Puni tekst: engleski, pdf (505 KB) str. 1631-1637 preuzimanja: 154* citiraj
APA 6th Edition
Khan, S.U., Rehman, O.U., Khan, N., Khan, A., Shah, S.A.A. i Yang, S. (2018). Improving the Diversity of PSO for an Engineering Inverse Problem using Adaptive Inertia Weight. Tehnički vjesnik, 25 (6), 1631-1637. https://doi.org/10.17559/TV-20170413135109
MLA 8th Edition
Khan, Shafi Ullah, et al. "Improving the Diversity of PSO for an Engineering Inverse Problem using Adaptive Inertia Weight." Tehnički vjesnik, vol. 25, br. 6, 2018, str. 1631-1637. https://doi.org/10.17559/TV-20170413135109. Citirano 21.10.2019.
Chicago 17th Edition
Khan, Shafi Ullah, Obaid Ur Rehman, Naeem Khan, Asfandyar Khan, Syed Anayat Ali Shah i Shiyou Yang. "Improving the Diversity of PSO for an Engineering Inverse Problem using Adaptive Inertia Weight." Tehnički vjesnik 25, br. 6 (2018): 1631-1637. https://doi.org/10.17559/TV-20170413135109
Harvard
Khan, S.U., et al. (2018). 'Improving the Diversity of PSO for an Engineering Inverse Problem using Adaptive Inertia Weight', Tehnički vjesnik, 25(6), str. 1631-1637. https://doi.org/10.17559/TV-20170413135109
Vancouver
Khan SU, Rehman OU, Khan N, Khan A, Shah SAA, Yang S. Improving the Diversity of PSO for an Engineering Inverse Problem using Adaptive Inertia Weight. Tehnički vjesnik [Internet]. 2018 [pristupljeno 21.10.2019.];25(6):1631-1637. https://doi.org/10.17559/TV-20170413135109
IEEE
S.U. Khan, O.U. Rehman, N. Khan, A. Khan, S.A.A. Shah i S. Yang, "Improving the Diversity of PSO for an Engineering Inverse Problem using Adaptive Inertia Weight", Tehnički vjesnik, vol.25, br. 6, str. 1631-1637, 2018. [Online]. https://doi.org/10.17559/TV-20170413135109

Sažetak
Particle swarm optimization is a stochastic optimal search algorithm inspired by observing schools of fishes and flocks of birds. It is prevalent due to its easy implementation and fast convergence. However, PSO has been known to succumb to local optima when dealing with complex and higher dimensional optimization problems. To handle the problem of premutature convergence in PSO, this paper presents a novel adaptive inertia weight strategy and modifies the velocity update equation with the new Sbest term. To maintain the diversity of the population a particular radius r is introduced to impulse cluster particles. To validate the effectiveness of the proposed algorithm, various test functions and typical engineering applications are employed, and the experimental results show that with the changing of the proposed parameter the performance of PSO improves when dealing with these complex and high dimensional problems.

Ključne riječi
adaptive inertia weight; global optimization; PSO; radius r, S best particle; Team 22

Hrčak ID: 212815

URI
https://hrcak.srce.hr/212815

Posjeta: 283 *