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

Studziński, Jan; Rojek, Izabela; Szeląg, Bartosz

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

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Title: 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

Abstract:

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.

Relation:

Raport Badawczy = Research Report

Detailed Resource Type:

Report

Resource Identifier:

oai:rcin.org.pl:208751

Source:

RB-2016-50-02

Language:

eng

Language of abstract:

eng

Rights:

Creative Commons Attribution BY 4.0 license

Terms of use:

Copyright-protected material. [CC BY 4.0] May be used within the scope specified in Creative Commons Attribution BY 4.0 license, full text available at: ; -

Digitizing institution:

Systems Research Institute of the Polish Academy of Sciences

Original in:

Library of Systems Research Institute PAS

Projects co-financed by:

Operational Program Digital Poland, 2014-2020, Measure 2.3: Digital accessibility and usefulness of public sector information; funds from the European Regional Development Fund and national co-financing from the state budget.

Access:

Open

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Last modified:

Oct 19, 2021

In our library since:

Sep 8, 2021

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All available object's versions:

https://rcin.org.pl/publication/245694

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Raporty Badawcze

Edition name	Date
RB-2016-50-02 : Studziński Jan, Rojek Izabela, Szeląg Bartosz : 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	Oct 19, 2021