Zobrazeno 1 - 10
of 16
pro vyhledávání: '"Gürcan Yavuz"'
Autor:
Gürcan Yavuz, Doğan Aydin
Publikováno v:
Applied Computational Intelligence and Soft Computing, Vol 2016 (2016)
Optimal feature subset selection is an important and a difficult task for pattern classification, data mining, and machine intelligence applications. The objective of the feature subset selection is to eliminate the irrelevant and noisy feature in or
Externí odkaz:
https://doaj.org/article/ae53c37b83e34cfdb9b2f23a1f7be812
Autor:
Gürcan Yavuz
Publikováno v:
IEEE Access. 10:103765-103780
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b7251065aae7c4d208df319d67b0f744
https://doi.org/10.1109/access.2022.3210122
https://doi.org/10.1109/access.2022.3210122
Publikováno v:
Volume: 27, Issue: 6 4797-4817
Turkish Journal of Electrical Engineering and Computer Science
Turkish Journal of Electrical Engineering and Computer Science
Infinite impulse response (IIR) system identification problem is defined as an IIR filter modeling to represent an unknown system. During a modeling task, unknown system parameters are estimated by metaheuristic algorithms through the IIR filter. Thi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4372567c0dd78d8638d344d936f93ba4
https://doi.org/10.3906/elk-1809-83
https://doi.org/10.3906/elk-1809-83
Autor:
Gürcan Yavuz
Publikováno v:
Journal of Computational Science. 60:101597
This study, incorporating three improvements into the structure of the original SSA algorithm to increase its exploration and exploitation capabilities, suggests an SSA variant algorithm named "Diversified Position Update Equation-Based SSA with Refr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7193f3ee2f9d3197390db20eca4bd219
https://doi.org/10.1016/j.jocs.2022.101597
https://doi.org/10.1016/j.jocs.2022.101597
Publikováno v:
Applied Soft Computing. 116:108343
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::845ee498115f27f8900b563d700533f1
https://doi.org/10.1016/j.asoc.2021.108343
https://doi.org/10.1016/j.asoc.2021.108343
Publikováno v:
Swarm Intelligence. 11:1-38
The artificial bee colony (ABC) algorithm is a popular metaheuristic that was originally conceived for tackling continuous function optimization tasks. Over the last decade, a large number of variants of ABC have been proposed, making it by now a wel
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::04a3c76f6c2ed8d893f9921fcbb6e672
https://doi.org/10.1007/s11721-017-0131-z
https://doi.org/10.1007/s11721-017-0131-z
Publikováno v:
SIU
Segmentation is a very important step in image processing. One of the segmentation methods is multi-level thresholding. The success of multi-level thresholding depends on the best way to determine the appropriate threshold values. In this study, we t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c6f78b7f1e2a87ea7d5609ae5cf0b113
https://doi.org/10.1109/siu.2018.8404586
https://doi.org/10.1109/siu.2018.8404586
Autor:
Gurcan Yavuz
Publikováno v:
Düzce Üniversitesi Bilim ve Teknoloji Dergisi, Vol 11, Iss 2, Pp 799-811 (2023)
Salp Sürü Algoritması (SSA) son dönem sürü zekâsı algoritmalarından olup, basit yapılıdır ve kullanımı oranı artan bir algoritmadır. Kullanım oranındaki artışın en önemli sebebi, bu algoritmanın problem çözmede gösterdiği b
Externí odkaz:
https://doaj.org/article/e04df309671f4caa86f9b50b78be9b5b
Publikováno v:
GECCO (Companion)
2017 Genetic and Evolutionary Computation Conference Companion, GECCO 2017 -- 15 July 2017 through 19 July 2017 -- -- 128763
ABC-X is a generalized, automatically configurable framework for the Artificial Bee Colony (ABC) metaheuristic. ABC-X ha
ABC-X is a generalized, automatically configurable framework for the Artificial Bee Colony (ABC) metaheuristic. ABC-X ha
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cb30573c7d7ee2abda6654f64a5dd49f
https://doi.org/10.1145/3067695.3082486
https://doi.org/10.1145/3067695.3082486