Analysis of Kinetic Parameters for the Water Treatment in Tokyo Bay Based on Machine Learning

Chenyang Lin

doi:10.54097/z9emz385

Authors

Chenyang Lin

DOI:

https://doi.org/10.54097/z9emz385

Keywords:

Water Treatment, Biomimetic Membrane, Machine Learning.

Abstract

Water contamination is an environmental problem that is being prompt in the global society. Exposure to contaminated water can hurt public health, due to the industrial, biological, and anthropogenic effects. Hence the advanced water treatment method has been raised to solve the contamination problem. Many techniques are being obtained to develop a method in engineering to solve the contamination problem on a site， and machine learning is also a tool to help with a high decision efficiency of the method construction. This study mainly focuses on the application of the MLP regressor and the MLP classifier on the water treatment in Tokyo Bay and the decision-making process during the water treatment construction. It has indicated that in the Tokyo Bay area, the aerobic bioremediation method works well. The Biological Biomimetic Membrane has the best predictability in the MLP classifier modal, and the Aerobic Bioremediation is appropriate for the selected observation sites in Tokyo Bay. Recent tests have shown that the real-time parameters selected in the field and the amount of data extracted have a significant impact on the water treatment method recommendation. In this paper, by applying the techniques of machine learning to specific scenarios, it provides new perspectives on the way of choosing conventional water treatment methods and improves the decision-making efficiency to a certain extent.

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