Cite

Alvarez-Aramberri, J., Pardo, D. and Barucq, H. (2013). Inversion of magnetotelluric measurements using multigoal oriented hp-adaptivity, Procedia Computer Science 18: 1564-1573.10.1016/j.procs.2013.05.324Search in Google Scholar

Barabasz, B., Gajda-Zagórska, E., Migórski, S., Paszyński, M., Schaefer, R. and Smołka, M. (2014). A hybrid algorithm for solving inverse problems in elasticity, International Journal of Applied Mathematics and Computer Science 24(4): 865-886, DOI: 10.2478/amcs-2014-0064.10.2478/amcs-2014-0064Search in Google Scholar

Beasley, D., Bull, D.R. and Martin, R.R. (1993). A sequential niche technique for multimodal function optimization, Evolutionary Computation 1(2): 101-125.10.1162/evco.1993.1.2.101Search in Google Scholar

Berenger, J.-P. (1994). A perfectly matched layer for the absortion of electromagnetic waves, Journal of Computational Physics 114(2): 185-200.10.1006/jcph.1994.1159Search in Google Scholar

Byrski, A., Schaefer, R., Smołka, M. and Cotta, C. (2013). Asymptotic guarantee of success for multi-agent memetic systems, Bulletin of the Polish Academy of Sciences: Technical Sciences 61(1): 257-278.10.2478/bpasts-2013-0025Search in Google Scholar

Cetnarowicz, K., Kisiel-Dorohinicki, M. and Nawarecki, E. (1996). The application of evolution process in multi-agent world (MAW) to the prediction system, in M. Tokoro (Ed.), Proceedings of the 2nd International Conference on Multiagent Systems (ICMAS-96), Menlo Park, CA, USA, pp. 26-32.Search in Google Scholar

Demkowicz, L. (2006). Computing with hp-Adaptive Finite Elements, Vol. 1: One and Two Dimensional Elliptic and Maxwell Problems, Chapman & Hall/CRC, Boca Raton, FL.10.1201/9781420011685Search in Google Scholar

Demkowicz, L., Kurtz, J., Pardo, D., Paszyński, M., Rachowicz, W. and Zdunek, A. (2007). Computing with hp-Adaptive Finite Elements, Vol. 2. Frontiers: Three Dimensional Elliptic and Maxwell Problems with Applications, Chapman & Hall/CRC, Boca Raton, FL.10.1201/9781420011692Search in Google Scholar

Ester, M., Kriegel, H.-P., Sander, J. and Xu, X. (1996). A density-based algorithm for discovering clusters in large spatial databases with noise, Proceedings of the 2nd International Conference on Knowledge Discovery and Data Mining KDD-96, Portland, OR, USA, pp. 226-231.Search in Google Scholar

FIPA (2002). Foundation for Intelligent Physical Agents (FIPA) Specifications, www.fipa.org.Search in Google Scholar

Gajda-Zagórska, E., Schaefer, R., Smołka, M., Paszyński, M. and Pardo, D. (2015). A hybrid method for inversion of 3D DC resistivity logging measurements, Natural Computing 14(3): 355-374. DOI: 10.1007/s11047-014-9440-y.10.1007/s11047-014-9440-y454171626300711Search in Google Scholar

Grochowski, M., Smołka, M. and Schaefer, R. (2006). Architectural principles and scheduling strategies for computing agent systems, Fundamenta Informaticae 71(1): 15-26.Search in Google Scholar

Jojczyk, P. and Schaefer, R. (2009). Global impact balancing in the hierarchic genetic search, Computing and Informatics 28(2): 181-193.Search in Google Scholar

Neri, F., Cotta, C. and Moscato, P. (Eds.) (2012). Handbook of Memetic Algorithms, Studies in Computational Intelligence, Vol. 379, Springer, Heidelberg.Search in Google Scholar

Obuchowicz, A. (1997). The evolutionary search with soft selection and deterioration of the objective function, Proceedings of the 6th International Conference on Intelligent Information Systems IIS’97, Zakopane, Poland, pp. 288-295.Search in Google Scholar

Pardo, D., Demkowicz, L., Torres-Verdín, C. and Tabarovsky, L. (2006). A goal-oriented hp-adaptive finite element method with electromagnetic applications, Part I: Electrostatics, International Journal for Numerical Methods in Engineering 65(8): 1269-1309.10.1002/nme.1488Search in Google Scholar

Schaefer, R. and Kołodziej, J. (2003). Genetic search reinforced by the population hierarchy, in K.A. De Jong, R. Poli and J. Rowe (Eds.), Foundations of Genetic Algorithms 7, Morgan Kaufman, San Francisco, CA, pp. 383-399.Search in Google Scholar

Smołka, M., Gajda-Zagórska, E., Schaefer, R., Paszyński, M. and Pardo, D. (2015). A hybrid method for inversion of 3D AC logging measurements, Applied Soft Computing 36: 442-456.10.1016/j.asoc.2015.06.055Search in Google Scholar

Smołka, M. and Schaefer, R. (2014). A memetic framework for solving difficult inverse problems, in A.I. Esparcia-Alcázar and A.M. Mora (Eds.), EvoApplications 2014, Lecture Notes in Computer Science, Vol. 8602, Springer, Berlin/Heidelberg, pp. 138-149.10.1007/978-3-662-45523-4_12Search in Google Scholar

Vozoff, K. (1972). The magnetotelluric method in the exploration of sedimentary basins, Geophysics 37(1): 98-141.10.1190/1.1440255Search in Google Scholar

Wierzba, B., Semczuk, A., Kołodziej, J. and Schaefer, R. (2003). Hierarchical genetic strategy with real number encoding, Proceedings of the 6th Conference on Evolutionary Algorithms and Global Optimization, Łagów, Poland, pp. 231-237.Search in Google Scholar

Wolny, A. and Schaefer, R. (2011). Improving population-based algorithms with fitness deterioration, Journal of Telecommunications and Information Technology 4: 31-44. Search in Google Scholar

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Mathematics, Applied Mathematics