Feature Extraction of Marine Water Pollution Based on Data Mining

Haixia Lin,Jianhong Cui,Xiangwei Bai

doi:10.3390/sym13020355

Abstract

The ocean occupies more than two-thirds of the earth’s area, providing a lot of oxygen and materials for human survival and development. However, with human activities, a large number of sewage, plastic bags, and other wastes are discharged into the ocean, and the problem of marine water pollution has become a hot topic in the world. In order to extract the characteristics of marine water pollution, this study proposed K-means clustering technology based on cosine distance and discrimination to study the polluted water. In this study, the polygonal area method combined with six parameters of water quality is used to analyze the marine water body anomalies, so as to realize the rapid and real-time monitoring of marine water body anomalies. At the same time, the cosine distance method and discrimination are used to classify marine water pollutants, so as to improve the classification accuracy. The results show that the detection rate of water quality anomalies is more than 88.2%, and the overall classification accuracy of water pollution is 96.3%, which proves the effectiveness of the method. It is hoped that this study can provide timely and effective data support for the detection of marine water bodies.

Highlights

With the unprecedented prosperity of international trade since the 20th century, the marine transportation industry has been greatly developed, and the marine oil spill pollution caused by marine oil tankers is becoming more and more serious
This study focuses on the identification of water pollution types, and the accuracy of discrimination classification is more than 95.6%, which is conducive to the rapid development of relevant treatment measures when marine water pollution occurs
The results show that the detection rates of heavy metal pollutants and phenol aniline pollutants are 94.7% and 97.8%, respectively, and the total classification accuracy of seawater pollutants is 96.3% under the

Summary

Introduction

With the unprecedented prosperity of international trade since the 20th century, the marine transportation industry has been greatly developed, and the marine oil spill pollution caused by marine oil tankers is becoming more and more serious. The discharge of a large amount of wastewater and garbage aggravates the degree of marine pollution. It can be said that all marine pollution is related to human activities. There is a certain lag in the current water quality monitoring technology, which is very unfavorable for the timely detection of marine water pollution. With the rapid development of big data technology, online water quality monitoring technology based on data mining has begun to develop, but the related research and application are limited. Under the existing technical means, it is very important to combine the data mining technology to extract and judge the water quality monitoring information efficiently

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Conclusion