岩矿测试2025，Vol.44Issue(3)：406-419,14.DOI:10.15898/j.ykcs.202409280204
GA-BP神经网络在精准刻画场地地下水污染物扩散范围的应用研究
Application of a GA-BP Neural Network in Accurately Characterizing the Diffusion Range of Groundwater Pollutants
摘要
Abstract
This study addresses the issue of unevenly distributed sampling points,which leads to inaccurate characterization of pollutant diffusion ranges.Using ArcGIS spatial interpolation,the distribution of Mn2+ions in a chemical park was analyzed,revealing discrepancies due to uneven sampling.To overcome this,two neural network models—GA-BP and standard BP—were applied to predict Mn2+concentrations at unsampled locations.The GA-BP neural network,optimized with a Genetic Algorithm,showed the best performance,filling gaps in data and allowing for a more accurate concentration distribution map.This revised map was used to delineate the Mn2+diffusion range,which was further validated with the known production and migration mechanisms of Mn2+.The results demonstrate that the GA-BP model significantly improves the accuracy of pollutant diffusion mapping and offers a more reliable method for environmental pollution assessment,especially in areas with limited sampling data.The BRIEF REPORT is available for this paper at http://www.ykcs.ac.cn/en/article/doi/10.15898/j.ykcs.202409280204.关键词
地下水/化工园区/GA-BP神经网络/扩散范围Key words
groundwater/chemical industrial park/GA-BP neural network/influence range分类
环境科学引用本文复制引用
季佳运,肖霄,杨品璐,刘洋,周亚红..GA-BP神经网络在精准刻画场地地下水污染物扩散范围的应用研究[J].岩矿测试,2025,44(3):406-419,14.基金项目
河北省省级科技计划项目(236Z4204G) （236Z4204G）
河北省自然科学基金项目(D2022403016) （D2022403016）
河北省教育厅科学研究项目(ZD2022119) （ZD2022119）
河北地质大学第二十届学生科研项目(KAG202402) （KAG202402）
