TY - GEN A1 - Studziński, Jan A1 - Rojek, Izabela A1 - Szeląg, Bartosz PB - Instytut Badań Systemowych. Polska Akademia Nauk PB - Systems Research Institute. Polish Academy of Sciences N1 - 3, 21-47 pages ; 21 cm N1 - Bibliography p. 44-47 N2 - In the present study the Support Vector Method (SVM) is used to analyze the dependency between input variables (quantity and quality of wastewaters at the inflow and operational characteristics of an Activated Sludge Tank (AST)) and a result of predicted mixed liquor suspended solid (MLSS) and substrate loads (FIM). Computations revealed, that the highest errors for MLSS are present if only the load of organie compounds susceptible to chemical degradation was included in the input data and lowest when load of coal, ammoniacal nitrogen, suspension and ASCh's operational characteristics were used as the input. Moreover, it appeared that indices of wastewater quality at the inflow to the treatment plant can be sirnulated on the basis of the measured discharge and temperature of wastewaters and in a result it is possible replacing these measured indices with modeled ones to sirnulated MLSS and FIM. The lowest 'errors of predicted substrate loads, computed on th.e basis of modeled using SVM indices values were obtained for coal, arnmoniacal nitrogen, suspension loads and AST's operational characteristics - sludge temperature and pH and methanol dosage. L1 - http://www.rcin.org.pl/Content/208751/PDF/RB-2016-50-02.pdf M3 - Text CY - Warszawa J2 - Raport Badawczy = Research Report ; RB/50/2016/02 PY - 2016 T1 - Prognozowanie dopływu ścieków surowych do oczyszczalni i ładunku zanieczyszczeń w ściekach za pomocą sieci neuronowych i modeli operatorowych * Modelling mixed liquor suspended solid and substrate load on the basis of wastewater quality in di ces and operational parameters of the bioreactor: data mining approach UR - http://www.rcin.org.pl/dlibra/publication/edition/208751 ER -