4 research outputs found

    Semi-multifractal optimization algorithm

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    Observations on living organism systems are the inspiration for the creation of modern computational techniques. The article presents an algorithm implementing the division of a solution space in the optimization process. A method for the algorithm operation controlling shows the wide range of its use possibilities. The article presents properties of fractal dimensions of subareas created in the process of optimization. The paper also presents the possibilities of using this method to determine function extremes. The approach proposed in the paper gives more opportunities for its use.Alrawi A, Sagheer A, Ibrahim D (2012) Texture segmentation based on multifractal dimension. Int J Soft Comput ( IJSC ) 3(1):1–10Belussi A, Catania B, Clementini E, Ferrari EE (eds) (2007) Spatial data on the web modeling and management. Springer, Berlin. doi: 10.1007/978-3-540-69878-4Corso G, Freitas J, Lucena L (2004) A multifractal scale-free lattice. Phys A Stat Mech Appl 342(1–2):214–220. doi: 10.1016/j.physa.2004.04.081Corso G, Lucena L (2005) Multifractal lattice and group theory. Phys A Stat Mech Appl 357(1):64–70. doi: 10.1016/j.physa.2005.05.049Gosciniak I (2017) Discussion on semi-immune algorithm behaviour based on fractal analysis. Soft Comput 21(14):3945–3956. doi: 10.1007/s00500-016-2044-yHwang WJ, Derin H (1995) Multiresolution multiresource progressive image transmission. IEEE Trans Image Process 4:1128–1140. doi: 10.1109/83.403418Iwanicki K, van Steen M (2009) Using area hierarchy for multi-resolution storage and search in large wireless sensor networks. In: Communications, 2009. ICC ’09. IEEE international conference on, pp 1–6. doi: 10.1109/ICC.2009.5199556Juliany J, Vose M (1994) The genetic algorithm fractal. Evol Comput 2(2):165–180. doi: 10.1162/evco.1994.2.2.165Kies P (2001) Information dimension of a population’s attractor a binary genetic algorithm. In: Artificial neural nets and genetic algorithms: proceedings of the international conference in Prague, Czech Republic. Springer, pp 232–235. doi: 10.1007/978-3-7091-6230-9_57Kotowski S, Kosinski W, Michalewicz Z, Nowicki J, Przepiorkiewicz B (2008) Fractal dimension of trajectory as invariant of genetic algorithms. In: Artificial intelligence and soft computing (ICAISC 2008). Springer, pp 414–425. doi: 10.1007/978-3-540-69731-2_41Lu Y, Huo X, Tsiotras P (2012) A beamlet-based graph structure for path planning using multiscale information. IEEE Trans Autom Control 57(5):1166–1178. doi: 10.1109/TAC.2012.2191836Marinov M, Kobbelt L (2005) Automatic generation of structure preserving multiresolution models. In: Eurographics, pp 1–8Masayoshi K, Masaru N, Yoshio S (1996) Identification of complicated shape objects by fractal characteristic variables categorizing dust particles on LSI wafer surface. Syst Comput Jpn 27(6):82–91. doi: 10.1002/scj.4690270608Michalewicz Z (1996) Genetic algorithms + data structures = evolution programs. Springer, Berlin. doi: 10.1007/978-3-662-03315-9Mo H (2008) Handbook of research on artificial immune systems and natural computing: applying complex adaptive technologies. Information Science Reference - Imprint of: IGI Publishing. doi: 10.4018/978-1-60566-310-4Pereira M, Corso G, Lucena L, Freitas J (2005) A random multifractal tilling. Chaos Solitons Fractals 23:1105–1110. doi: 10.1016/j.chaos.2004.06.045Rejaur Rahman M, Saha SK (2009) Multi-resolution segmentation for object-based classification and accuracy assessment of land use/land cover classification using remotely sensed data. J Indian Soc Remote Sens 36:189–201. doi: 10.1007/s12524-008-0020-4Song J, Qian F (2006) Fractal algorithm for finding global optimal solution. In: International conference on computational intelligence for modelling control and automation, and international conference on intelligent agents, web technologies and internet commerce (CIMCA–IAWTIC’06). IEEE Computer Society, pp 149–153Urrutia J, Sack JR (eds) (2000) Handbook of computational geometry. North-Holland, Amsterdam. doi: 10.1016/B978-0-444-82537-7.50027-9Weise T (2009) Global Optimization Algorithms—Theory and Applications, 2nd edn. University of Kassel, Distributed Systems Group. http://www.it-weise.deWeller R (2013) New geometric data structures for collision detection and haptics. Springer, Cham. doi: 10.1007/978-3-319-01020-5Vujovic I (2014) Multiresolution approach to processing images for different applications: interaction of lower processing with higher vision. Springer, Cham. doi: 10.1007/978-3-319-14457-3 Google Scholar Virtual library of simulation experiments: test functions and datasets, optimization test problems. https://www.sfu.ca/ssurjano/optimization.html. Accessed 28 July 201

    Abstracts on Radio Direction Finding (1899 - 1995)

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    The files on this record represent the various databases that originally composed the CD-ROM issue of "Abstracts on Radio Direction Finding" database, which is now part of the Dudley Knox Library's Abstracts and Selected Full Text Documents on Radio Direction Finding (1899 - 1995) Collection. (See Calhoun record https://calhoun.nps.edu/handle/10945/57364 for further information on this collection and the bibliography). Due to issues of technological obsolescence preventing current and future audiences from accessing the bibliography, DKL exported and converted into the three files on this record the various databases contained in the CD-ROM. The contents of these files are: 1) RDFA_CompleteBibliography_xls.zip [RDFA_CompleteBibliography.xls: Metadata for the complete bibliography, in Excel 97-2003 Workbook format; RDFA_Glossary.xls: Glossary of terms, in Excel 97-2003 Workbookformat; RDFA_Biographies.xls: Biographies of leading figures, in Excel 97-2003 Workbook format]; 2) RDFA_CompleteBibliography_csv.zip [RDFA_CompleteBibliography.TXT: Metadata for the complete bibliography, in CSV format; RDFA_Glossary.TXT: Glossary of terms, in CSV format; RDFA_Biographies.TXT: Biographies of leading figures, in CSV format]; 3) RDFA_CompleteBibliography.pdf: A human readable display of the bibliographic data, as a means of double-checking any possible deviations due to conversion
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