Neural networks in economic analyses of wastewater systems

During selection of optimum sewerage and wastewater treatment systems in rural settlements, often a large number of potential technical solutions is generated. The economic criterion is most frequently assigned the greatest importance which finally results that the solutions involving the lowest total costs are preferred. The conventional approach considerably complicates the choice of the optimum solution, because it requires great efforts in determining the size of considered solutions and preparing of corresponding cost estimates. per analyzes the possibility of using of neural networks in economic analyses of wastewater systems. The neural network NENECOS (NEural Network for approximate Estimation of COsts of wastewater Systems) has been created, which allows simple, fast and adequately accurate estimation of total or unit costs of construction, operation and maintenance of sewerage systems, without the need for prior sizing and preparing of cost estimates. This allows simple and more efficient economic comparison of a greater number of alternative solutions. The limitation of the neural network NENECOS is the possibility of approximate estimation only for smaller rural settlements up to 500 population equivalents.