基于机器学习的西藏某污水处理厂进水水质预测研究  

Research on Prediction of Intake Water Quality of a Sewage Treatment Plant in Tibet Based on Machine Learning

作　　者：王娜[1,2,3] 韩帅 吴玉龙[1] WANG Na;HAN Shuai;WU Yulong(College of Information Engineering,Xizang Minzu University,Xianyang Shaanxi 712082,China;Key Laboratory of Water Safety and Aquatic Ecosystem Health of Xizang,Xianyang Shaanxi 712082,China;Key Laboratory of Water Pollution Control and Ecological Restoration of Xizang,National Ethnic Affairs Commission,Xizang Minzu University,Xianyang Shaanxi 712082,China)

机构地区：[1]西藏民族大学信息工程学院,陕西咸阳712082 [2]西藏自治区水质安全与水环境健康重点实验室,陕西咸阳712082 [3]西藏民族大学西藏水污染控制与生态修复国家民委重点实验室,陕西咸阳712082

出　　处：《信息与电脑》2025年第1期10-13,共4页Information & Computer

基　　金：西藏民族大学校内科研项目“基于LSTM神经网络的污水处理厂水质预测及可视化系统设计”(项目编号:24MDY08)。

摘　　要：高原地区的高寒、高海拔条件带来了平均温度低、氧含量低和气压低的“三低”特殊环境,导致高原地区污水处理面临达标困难的问题。水质预测是污水防治的基础,提高水质预测精度,能够为污水处理提供重要决策支持。文章首先对西藏某污水处理厂水质特征进行分析;其次,基于决策树回归、支持向量回归及随机森林回归等机器学习模型,对污水处理厂进水化学需氧量和总氮进行预测;最后,对预测结果进行对比分析。研究表明,支持向量回归和随机森林回归在污水处理厂水质预测方面均具有良好的适用性,能够为污水处理厂运行决策提供有益参考。The high cold and high-altitude conditions in high-altitude areas have brought about a special environment of“three lows”:low average temperature,low oxygen content,and low air pressure,which makes it difficult for sewage treatment in high-altitude areas to meet standards.Water quality prediction is the foundation of sewage prevention and control.Improving the accuracy of water quality prediction can provide important decision support for sewage treatment.Firstly,the water quality characteristics of a sewage plant in Xizang are analyzed;Secondly,machine learning models such as decision tree regression,support vector regression,and random forest regression are used to predict the influent chemical oxygen demand and total nitrogen of sewage treatment plants;Finally,compare and analyze the predicted results.Research has shown that both support vector regression and random forest regression have good applicability in predicting water quality in sewage treatment plants,and can provide useful references for decision-making in the operation of sewage treatment plants.

关 键 词：机器学习 污水处理厂 进水水质 高原地区 

分 类 号：TP181[自动化与计算机技术—控制理论与控制工程]