0449025 20240103210936.920151023235959.9 1 s. P cav_un_epca*0449038978-2-910239-82-45--2015AntochJ. data analysis mathematical gnostics robust methods cav_un_auth*0103409 Wagner Zdeněk Laboratoř separačních procesů E. Hály E. Hála Laboratory of Separation Processes UCHP-M Department of Aerosols Chemistry and Physics Ústav chemických procesů AV ČR, v. v. i. cav_un_auth*0101135 Kovanic Pavel Rozpoznávání obrazu Department of Pattern Recognition RO RO UTIA-B Ústav teorie informace a automatizace AV ČR, v. v. i. One of the principal tasks of nowaday's industry is process intensification. The methodology for finding reliable results is highly demanded. While marketing is concentrated on analysis big data that are available in eShops as well as other internet media, the situation in the industry is different because solution must be found in real time based on limited amount of data. The algorithms of data analysis must therefore be fast and robust. In the last few decades statistical methods have advanced considerably but a new, nonstatistical approach to uncertainty, called mathematical gnostics, have also be developed. This new approach is based upon the fundamental laws of nature and robustness is its inherent property. The contribution will present several applications with the emphasis laid upon description of the main features of mathematical gnostics. Previous applications in energetics that can be enhanced by use of the modern algorithms of data analysis will also be mentioned. cav_un_auth*0320897 Modelling Smard Grids 2015 Prague 10.09.2015-11.09.2015 CZ 2016 BA 4 O nusl 4on 20231122141230.0 PO RVO:67985858 RVO:67985556 http://hdl.handle.net/11104/0250606 S 2015 Soubory v repozitáři: SKMBT_C22015101209580.pdf cav_un_epca*0449038 Abstracts Book 978-2-910239-82-4 5 - - 2015 Antoch J. 340