Implementation of an environmental decision support system for controlling the pre-oxidation step at a full-scale drinking water treatment plant.
Water Sci Technol
; 81(8): 1778-1785, 2020 Apr.
Article
in En
| MEDLINE
| ID: mdl-32644970
ABSTRACT
Drinking water treatment plants (DWTPs) face changes in raw water quality, and treatment needs to be adjusted to produce the best water quality at the minimum environmental cost. An environmental decision support system (EDSS) was developed for aiding DWTP operators in choosing the adequate permanganate dosing rate in the pre-oxidation step. To this end, multiple linear regression (MLR) and multi-layer perceptron (MLP) models are compared for choosing the best predictive model. Besides, a case-based reasoning (CBR) model was approached to provide the user with a distribution of solutions given similar operating conditions in the past. The predictive model consisted of an MLP and has been validated against historical data with sufficient good accuracy for the utility needs (R2 = 0.76 and RSE = 0.13 mg·L-1). The integration of the predictive and the CBR models in an EDSS gives the user an augmented decision-making capacity of the process and has great potential for both assisting experienced users and for training new personnel in deciding the operational set-point of the process.
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Drinking Water
/
Water Purification
Type of study:
Prognostic_studies
/
Sysrev_observational_studies
Aspects:
Implementation_research
Language:
En
Journal:
Water Sci Technol
Journal subject:
SAUDE AMBIENTAL
/
TOXICOLOGIA
Year:
2020
Document type:
Article
Affiliation country:
España