基于随机森林耦合因子分析的供水管网健康风险评价方法

Health Risk Assessment Model for Water Supply Network Based on Random Forest Coupling Factor Analysis

随着市政供水管网的规模扩大,城市供水管网的风险不断提高,亟须科学地评估其健康风险。考虑到大数据背景下供水管网数据的样本量和维度呈增长趋势,文章通过将因子分析和随机森林耦合到同一体系框架中,构建供水管网健康风险评价模型,并以上海市HP区供水管网为例进行了计算分析。研究结果表明,耦合模型的准确率和召回率达到了87.50%和94.12%,说明该模型能够有效地预测供水管网健康风险概率;根据重要性分析和敏感性分析的结果发现,管龄与管材是影响管网健康风险的关键因素。文章提出的城市供水管网健康风险评价方法耦合了因子分析的特征简化优势与随机森林的高准确性预测能力,为供水企业进行管网的管理维护、更新改造提供了一定的量化依据。

With the expansion of municipal water supply network,the risk of urban water supply network is increasing,and it is urgent to evaluate its health risk scientifically.Considering the increasing sample size and dimensions of water supply network data in the context of big data,this paper coupled factor analysis and random forest into the same system framework to construct a health risk assessment model for water supply network,and took the HP District water supply network in Shanghai as an example for calculation and analysis.The results showed that the accuracy and recall rates of the coupled model were 87.50%and 94.12%,indicating that the model could effectively predict the health risk probability of water supply network.According to the results of importance analysis and sensitivity analysis,it was found that pipe age and pipe material were the key factors affecting the health risk of pipe network.The health risk assessment method of urban water supply network proposed in this paper combines the feature simplification advantage of factor analysis with the high accuracy prediction ability of random forest,and provides a certain quantitative basis for water supply enterprises to carry out the management,maintenance,renovation and reconstruction of water supply network.