Chaos driven PSO – On the influence of various CPRNG implementations – An initial study

Pluháček, Michal; Šenkeřík, Roman; Zelinka, Ivan; Davendra, Donald David

dc.title	Chaos driven PSO – On the influence of various CPRNG implementations – An initial study	en
dc.contributor.author	Pluháček, Michal
dc.contributor.author	Šenkeřík, Roman
dc.contributor.author	Zelinka, Ivan
dc.contributor.author	Davendra, Donald David
dc.relation.ispartof	ISCS 2014: Interdisciplinary Symposium on Complex Systems
dc.relation.ispartof	Emergence, Complexity and Computation
dc.identifier.issn	2194-7287 Scopus Sources, Sherpa/RoMEO, JCR
dc.identifier.issn	2194-7295 Scopus Sources, Sherpa/RoMEO, JCR
dc.identifier.isbn	978-3-319-10758-5
dc.identifier.isbn	978-3-319-10759-2
dc.date.issued	2015
dc.citation.spage	225
dc.citation.epage	237
dc.type	bookPart
dc.language.iso	en
dc.publisher	Springer International Publishing
dc.identifier.doi	10.1007/978-3-319-10759-2_24
dc.relation.uri	https://link.springer.com/chapter/10.1007/978-3-319-10759-2_24
utb.faculty	Faculty of Applied Informatics
dc.identifier.uri	http://hdl.handle.net/10563/1008144
utb.identifier.rivid	RIV/70883521:28140/14:43871474!RIV15-MSM-28140___
utb.identifier.obdid	43871689
utb.source	c-crossref
dc.date.accessioned	2018-08-29T08:26:55Z
dc.date.available	2018-08-29T08:26:55Z
utb.ou	CEBIA-Tech
utb.contributor.internalauthor	Pluháček, Michal
utb.contributor.internalauthor	Šenkeřík, Roman
utb.contributor.internalauthor	Zelinka, Ivan
utb.fulltext.affiliation	Michal Pluhacek 1 , Roman Senkerik 1 , Ivan Zelinka 1 , and Donald Davendra 2 1 Faculty of Applied Informatics, Tomas Bata University in Zlin, T.G. Masaryka 5555, 760 01 Zlin, Czech Republic {pluhacek,senkerik,zelinka}@fai.utb.cz 2 Faculty of Electrical Engineering and Computer Science, VŠB-Technical University of Ostrava, 17. listopadu 15, 708 33 Ostrava-Poruba, Czech Republic donald.davendra@vsb.cz
utb.fulltext.dates	-
utb.fulltext.references	1. Kennedy, J., Eberhart, R.: Particle Swarm Optimization. In: Proceedings of IEEE International Conference on Neural Networks, vol. IV, pp. 1942–1948 (1995) 2. Dorigo, M., Gambardella, L.M., Birattari, M., Martinoli, A., Poli, R., Stützle, T. (eds.): ANTS 2006. LNCS, vol. 4150. Springer, Heidelberg (2006) 3. Eberhart, R., Kennedy, J.: Swarm Intelligence. The Morgan Kaufmann Series in Artificial Intelligence. Morgan Kaufmann (2001) 4. Goldberg, D.E.: Genetic Algorithms in Search Optimization and Machine Learning, p. 41. Addison Wesley (1989) ISBN 0201157675 5. Storn, R., Price, R.: Differential evolution - a simple and efficient heuristic for global optimization over continuous spaces. Journal of Global Optimization 11, 341–359 (1997) 6. Shi, Y.H., Eberhart, R.C.: A modified particle swarm optimizer. In: IEEE International Conference on Evolutionary Computation, Anchorage Alaska, pp. 69–73 (1998) 7. Nickabadi, A., Ebadzadeh, M.M., Safabakhsh, R.: A novel particle swarm optimization algorithm with adaptive inertia weight. Applied Soft Computing 11(4), 3658–3670 (2011) ISSN 1568-4946 8. Zelinka, I.: SOMA - self organizing migrating algorithm. In: Babu, B.V., Onwubolu, G. (eds.) New Optimization Techniques in Engineering, ch. 7, vol. 33. Springer (2004) ISBN: 3-540-20167X 9. Caponetto, R., Fortuna, L., Fazzino, S., Xibilia, M.G.: Chaotic sequences to improve the performance of evolutionary algorithms. IEEE Transactions on Evolutionary Computation 7(3), 289–304 (2003) 10. Davendra, D., Zelinka, I., Senkerik, R.: Chaos driven evolutionary algorithms for the task of PID control. Computers & Mathematics with Applications 60(4), 1088–1104 (2010) ISSN 0898-1221 11. Araujo, E., Coelho, L.: Particle swarm approaches using Lozi map chaotic sequences to fuzzy modelling of an experimental thermal-vacuum system. Applied Soft Computing 8(4), 1354–1364 (2008) 12. Alatas, B., Akin, E., Ozer, B.A.: Chaos embedded particle swarm optimization algorithms. Chaos, Solitons & Fractals 40(4), 1715–1734 (2009) ISSN 0960-0779 13. Pluhacek, M., Senkerik, R., Davendra, D., Kominkova Oplatkova, Z., Zelinka, I.: On the behavior and performance of chaos driven PSO algorithm with inertia weight. Computers and Mathematics with Applications (2013), doi:10.1016/j.camwa.2013.01.016 (Article in press) 14. Pluhacek, M., Budikova, V., Senkerik, R., Oplatkova, Z., Zelinka, I.: On The Performance Of Enhanced PSO Algorithm With Lozi Chaotic Map – An initial Study. In: Proceedings of the 18th International Conference on Soft Computing, MENDEL 2012, pp. 40–45 (2012) ISBN 978-80-214-4540-6 15. Pluhacek, M., Senkerik, R., Zelinka, I., Davendra, I.D.: Chaos PSO algorithm driven alternately by two different chaotic maps - An initial study. In: 2013 IEEE Congress on Evolutionary Computation (CEC), pp. 2444–2449 (2013), doi:10.1109/CEC.2013.6557862, ISBN: 978-1-4799-0451-8 16. Pluhacek, M., Senkerik, R., Zelinka, I., Davendra, D.: New Adaptive Approach for Chaos PSO Algorithm Driven Alternately by Two Different Chaotic Maps – An Initial Study. In: Zelinka, I., Chen, G., Rössler, O.E., Snasel, V., Abraham, A. (eds.) Nostradamus 2013: Prediction, Model. & Analysis. AISC, vol. 210, pp. 77–87. Springer, Heidelberg (2013) 17. Sprott, J.C.: Chaos and Time-Series Analysis. Oxford University Press (2003) 18. Aziz-Alaoui, M.A., Robert, C., Grebogi, C.: Dynamics of a Hénon–Lozi-type map. Chaos, Solitons & Fractals 12(12), 2323–2341 (2001) ISSN 0960-0779
utb.fulltext.sponsorship	The following grants are acknowledged for the financial support provided for this research: Grant Agency of the Czech Republic - GACR P103/13/08195S, is partially supported by Grant of SGS No. SP2014/159 and SGS No. SP2014/170 Czech Republic, by the Development of human resources in research and development of latest soft computing methods and their application in practice project, reg. no. CZ.1.07/2.3.00/20.0072 funded by Operational Programme Education for Competitiveness, co-financed by ESF and state budget of the Czech Republic, further was supported by European Regional Development Fund under the project CEBIA-Tech No. CZ.1.05/2.1.00/03.0089 and by Internal Grant Agency of Tomas Bata University under the project No. IGA/FAI/2014/010.
utb.fulltext.projects	GACR P103/13/08195S
utb.fulltext.projects	SGS SP2014/159
utb.fulltext.projects	SGS SP2014/170
utb.fulltext.projects	CZ.1.07/2.3.00/20.0072
utb.fulltext.projects	CZ.1.05/2.1.00/03.0089
utb.fulltext.projects	IGA/FAI/2014/010