Gross parameters prediction of a granular attached biomass reactor through evolutionary polynomial regression

Heavy fluctuations in wastewater composition, such as those typical of tourist areas, can lead to a deteri- orationintreatmentplantperformanceifnoactionistakeninadvance.Mathematicalmodelling,applied to treatment plant performance prediction, can provide valuable information to address the stress issue. The present study shows that the evolutionary polynomial regression methodology (EPR) is able to pre- dicttheperformancesofanattachedgranularbiomasssystemsothatitispossibletomakethenecessary operatingchangesinadvance,avoidingdeteriorationinthequalityoftheeffluentdischarged.Thepresent papershowstheresultsofEPRapplicationtogrossparametersofagranularattachedbiomassreactor.For each parameter, a model capable of predicting the effluent value was assessed, based on the knowledge oftheinfluentcharacteristics.Coefficientsofdeterminationvalues(CoD)obtainedduringthemodelsval- idation phase, can be said to be more than satisfactory, varying between 84.2% and 94.6%. Moreover, the applied tests showed typical behaviours commonly found when observed and predicted values are quite similar. This paper reports the first application attempt for modelling this kind of emerging treatment system and gross parameters.