인공신경망 및 물질수지 모델을 활용한 하수처리 프로세스 시뮬레이터 구축

서지정보

ㆍ발행기관 : 대한상하수도학회 ㆍ수록지정보 : 상하수도학회지 / 29권 / 3호
ㆍ저자명 : 김정률, 이재현, 오재일

영어 초록

Developing two process models to simulate wastewater treatment process is needed to draw a comparison between measured BOD data and estimated process model data: a mathematical model based on the process mass-balance and an ANN (artificial neural network) model. Those two types of simulator can fit well in terms of effluent BOD data, which models are formulated based on the distinctive five parameters: influent flow rate, effluent flow rate, influent BOD concentration, biomass concentration, and returned sludge percentage. The structuralized mass-balance model and ANN modeI with seasonal periods can estimate data set more precisely, and changing optimization algorithm for the penalty could be a useful option to tune up the process behavior estimations. An complex model such as ANN model coupled with mass-balance equation will be required to simulate process dynamics more accurately.

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