Decision Making Model for Municipal Wastewater Conventional Secondary Treatment with Bayesian Networks
Edgardo Medina (Autonomous University of Mexico State, Toluca)
Carlos Roberto Fonseca (Autonomous University of Mexico State, Toluca)
Iván Gallego-Alarcón (Autonomous University of Mexico State, Toluca)
O Morales Napoles (TU Delft - Hydraulic Structures and Flood Risk)
Miguel A. Gómez-Albores (Autonomous University of Mexico State, Toluca)
Mario Esparza-Soto (Autonomous University of Mexico State, Toluca)
Carlos Alberto Mastachi-Loza (Autonomous University of Mexico State, Toluca)
Daury García-Pulido (Autonomous University of Mexico State, Toluca)
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Abstract
Technical, economic, regulatory, environmental, and social and political interests make the process of selecting an appropriate wastewater treatment technology complex. Although this problem has already been addressed from the dimensioning approach, our proposal in this research, a model of decision making for conventional secondary treatment of municipal wastewater through continuous-discrete, non-parametric Bayesian networks was developed. The most suitable network was structured in unit processes, independent of each other. Validation, with data in a mostly Mexican context, provided a positive predictive power of 83.5%, an excellent kappa (0.77 > 0.75), and the criterion line was surpassed with the location of the model in a receiver operating characteristic (ROC) graph, so the model can be implemented in this region. The final configuration of the Bayesian network allows the methodology to be easily extended to other types of treatments, wastewater, and to other regions.
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