Optimization of Water Quality Monitoring Networks Using Metaheuristic Approaches: Moscow Region Use Case

Currently many countries are struggling to rationalize water quality monitoring stations which is caused by economic demand. Though this process essential indeed, the exact elements of system be optimized without a subsequent and accuracy loss still remain obscure. Therefore, accurate historical data on groundwater pollution required detect monitor considerable environmental impacts. To collect such appropriate sampling assessment methodologies with an optimum spatial distribution augmented should exploited. Thus, configuration points number now considered as fundamental optimization challenge. The paper offers tests metaheuristic approaches for procedure multi-factors in “New Moscow” area. It shown that algorithms allow us reduce size training sample set, so area can halved. Moreover, reducing dataset improved prediction 20%. obtained results convincingly demonstrate proposed dramatically decrease total cost analysis dampening could recommended purposes.