文章基本信息

标题：Research on Urban Rainfall Runoff Pollution Prediction Model Based on Feature Fusion
本地全文：下载
作者：Junping Yao ; Tianle Sun
期刊名称：Discrete Dynamics in Nature and Society
印刷版ISSN：1026-0226
电子版ISSN：1607-887X
出版年度：2020
卷号：2020
页码：1-9
DOI：10.1155/2020/8861288
出版社：Hindawi Publishing Corporation
摘要：In this paper, a rainfall runoff pollution prediction method based on grey neural network algorithm is proposed in consideration of the current situation that the accuracy of research results related to rainfall runoff pollution prediction needs to be improved. Meanwhile, the characteristics of rainfall runoff pollution are analyzed from the perspectives of the main sources of rainfall runoff pollution, the types of rainfall runoff pollution, and the initial erosion. The neural network algorithm is optimized and trained according to the sample data to obtain the sample features; the sample data are predicted according to the extracted sample features, and the prediction model is generated by using the feature fusion technology for two groups of prediction results to generate the prediction model and realize the water drop prediction. The pollution concentration of runoff was obtained by the exponential function method. The experimental results show that the predicted values of discharge and pollution concentration are well fitted with the actual values, indicating that the proposed method has high accuracy and feasibility. Finally, from the viewpoint of non-engineering measures and engineering measures, the suggestions for treating runoff pollution and relevant supports for ecological environment protection are given.