基于双层神经网络与GIS可视化的土壤重金属污染评价

    Pollution assessment of heavy metals based on double-layer

    • 摘要: 针对土壤重金属污染进行评价,以四川省川芎主产区为例,对川芎主产区—都江堰、崇州、新都等15地土壤的重金属元素取样检测分析,采用双层组合神经网络和GIS空间分析技术综合评价川芎主产区土壤重金属污染。结果表明:研究区大部分区域处于轻度重金属污染状态,处于中度污染状态的区域为崇州、都江堰和彭州。基于双层组合BP神经网络和GIS的研究方法,可以在只具有少量数据的情况下对数据进行比较精确的空间分析,能够在满足一定精度分析的原则下适当的降低采样分析成本,得到比单因子指数评价准确度更高的空间分布图。

       

      Abstract: In order to assess the extent of heavy metals contamination resulting from geo-authentic productive area of Ligusticum chuanxiong Hort. in Sichuan province, fifteen soil samples were collected and analyzed for the content of the heavy metals. The assessment of heavy metals contamination in soils was performed by double-layer back propagation neutral network and GIS spatial analysis technology. The results of assessment indicated that most of research area was contaminated lightly. The areas of Chouzhou, Dujiangyan and Pengzhou were polluted in middling extent. The way of double-layer BPNN and GIS could carry out a relatively accurate spatial analysis to even a small group of data, reduce the cost of sampling under the principia of a stated analysis precision and get higher accuracy spatial distribution than the single-factor index method.

       

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