STATISTICALLY GUIDED ARTIFICIAL BEE COLONY ALGORITHM

Barış KOÇER

Öz


Artificial Bee Colony algorithm is one of the naturally inspired meta heuristic method. As usual, in a meta heuristic method, intuitively appealing way to have better results is extending calculation time or increasing the fitness evaluation count. But the desired way is acquiring better results with less computation. So in this work a modified Artificial Bee Colony algorithm which can find better results with same computation is developed by benefiting statistical observations.

Anahtar Kelimeler


Swarm intelligence; meta heuristic algorithms; artificial bee colony algorithm

Tam Metin:

PDF (English)

Referanslar


Akay, B., Karaboga, D., A modified artificial bee colony algorithm for real-parameter optimization, Information Sciences (2010), doi:10.1016/j.ins.2010.07.015

Basturk, B., Karaboga, D., An artificial bee colony (abc) algorithm for numeric function optimization, IEEE Swarm Intelligence Symposium 2006 (Indianapolis, Indiana, USA), May 2006.

Dorigo, M., Maniezzo, V., Colorni, A., Positive feedback as a search strategy, Technical Report 91-016, Politecnico di Milano, Italy, 1991.

Drias, H., Sadeg, S., Yahi, S., Cooperative bees swarm for solving the maximum weighted satisfiability problem, computational intelligence and bioinspired systems. in: 8th International Workshop on Artificial Neural Networks IWANN 2005, Vilanova, Barcelona, Spain, June 8–10 2005.

Fenglei, L., Haijun, D., Xing, F., The parameter improvement of bee colony algorithm in TSP problem, Science Paper Online, November 2007.

Holland, J.H., Adaptation in Natural and Artificial Systems, University of Michigan Press, Ann Arbor, MI, 1975.

Karaboga, D., An idea based on honeybee swarm for numerical optimization, Technical Report TR06, Erciyes University, Engineering Faculty, Computer Engineering Department, 2005.

Karaboga, D., Basturk, B., A powerful and efficient algorithm for numerical function optimization: artificial bee colony (ABC) algorithm, Journal of Global Optimization 39 (3) (2007) 459–471.

Karaboga, D., Akay, B., Solving large scale numerical problems using artificial bee colony algorithm, in: Sixth International Symposium on Intelligent and Manufacturing Systems Features, Strategies and Innovation (Sakarya, Turkiye), October 14–17, 2008.

Karaboga, D., Akay, B., An artificial bee colony (abc) algorithm on training artificial neural networks, in: 15th IEEE Signal Processing and Communications Applications, SIU 2007 (Eskisehir, Turkiye), June 2007, pp. 1–4.

Karaboga, D., Basturk, B., On the performance of artificial bee colony (ABC) algorithm, Applied Soft Computing 8 (1) (2008) 687–697.

Karaboga, D., Akay, B., Ozturk, C., Modeling decisions for artificial intelligence, Artificial Bee Colony (ABC) Optimization Algorithm for Training Feed-Forward Neural Networks, LNCS 4617/2007, Springer-Verlag, 2007, pp. 318–329.

Karaboga, D., Ozturk, C., Akay, B., Training neural networks with ABC optimization algorithm on medical pattern classification, in: International Conference on Multivariate Statistical Modelling and High Dimensional Data Mining (Kayseri, TURKEY), June 19–23, 2008.

Kennedy, J., Eberhart, R.C., in: Particle Swarm Optimization, 1995 IEEE International Conference on Neural Networks, vol. 4, 1995, pp. 1942–1948.

Lucic, P., Teodorovic´, D., Transportation modeling: an artificial life approach, in: ICTAI, 2002, pp. 216–223.

Ozturk, C., Karaboga, D., Classification by neural networks and clustering with artificial bee colony (ABC) algorithm, in: Sixth International Symposium on Intelligent and Manufacturing Systems Features, Strategies and Innovation (Sakarya, Turkiye), October 14–17, 2008

Teodorovic´ , D., Transport modeling by multi-agent systems: a swarm intelligence approach, Transportation Planning and Technology 26 (4) (2003).

Yang, X.S., Engineering optimizations via nature-inspired virtual bee algorithms, in: Artificial Intelligence and Knowledge Engineering Applications: A Bioinspired Approach, LNCS, vol. 3562/2005, June 2005, pp. 317– 323.


Madde Ölçümleri

Ölçüm Çağırılıyor ...

Metrics powered by PLOS ALM

Refback'ler



Telif Hakkı (c) 2017 Selçuk Üniversitesi Mühendislik, Bilim ve Teknoloji Dergisi

Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Tarayan Veri Tabanları

   ResearchBib 中国知网BASE Logo googleDirectory of Research Journals Indexing LogoOnline Access to Research in the EnvironmentDTUbroadcastlogo PBN - BETA versionjournal tocs uk ile ilgili görsel sonucuFind in a library with WorldCatDiscovery: Library search made simple. Return to JournalSeek Homejatstech ile ilgili görsel sonucuExLibris header imageStanford University Libraries