Construction of a Model for Water Purification Mechanisms in a River by Using a Neural Network Approach

Abstract

A model for purification mechanisms in a river was proposed to express changes in the values of BOD (Biochemical Oxygen Demand), COD (Chemical Oxygen Demand), T-N (Total Nitrogen), and T-P (Total Phosphorous) as the combination of inflows, streams, and weirs. Because expressions for these functions are unknown, the model first constructs multi-layer neural-network functions based on observations, and then uses the derivatives to evaluate the cause and effect of pollution.
For data of the Tamagawa through Tokyo, Japan in 2002, the model suggested that the cause of pollution is inflows from sewage, the stream of the Tamagawa has purification functions for COD and T-P, but has little ability for T-N, and the weirs have purification for COD, but have no purification for T-N and T-P. The results from the model were consistent with common sense for the water quality, and thus, there was no failure in the model.