基于机器学习的工业园区水污染源识别方法研究  

Research on the Identification Method of Water Pollution Source in Industrial Park Based on Machine Learning

作　　者：冯桐桐 Feng Tongtong(Beijing Huan’an Engineering Testing Co.,LTD.,Beijing 100020,China)

机构地区：[1]北京环安工程检测有限责任公司,北京100020

出　　处：《黑龙江科学》2025年第4期150-152,共3页Heilongjiang Science

摘　　要：针对工业园区水污染源识别难度大、准确率低等问题,提出一种基于机器学习的水污染源识别方法。通过构建水质参数指标体系,设计污染物特征数据采集与预处理方案,采用多种机器学习算法,对水质数据进行建模分析。开发了水污染源识别系统并进行实验验证,结果表明,该方法能够有效提高污染源识别的准确率,准确率达到90%以上,为工业园区水污染治理提供新的技术支持。In view of the difficulty and low accuracy of water pollution identification in industrial parks,the study proposes a method of water pollution identification based on machine learning.By constructing the water quality parameter index system,the pollutant characteristic data collection and pretreatment scheme is designed,and various machine learning algorithms are used to model and analyze the water quality data.The water pollution source identification system is developed and experimentally verified.The results show that this method can effectively improve the accuracy of pollution source identification,with the accuracy of more than 90%,and provide new technical support for water pollution control in industrial parks.

关 键 词：水污染源识别 机器学习 工业园区 水质参数 污染物特征 

分 类 号：X52[环境科学与工程—环境工程] X820.4