CAJ | 학술논문

根据湖南省多目标地球化学调查资料，研究了易家湾地区表层土壤中重金属元素As， Cd，Hg，Pb，Zn 的污染状况并寻找污染源。利用地累积指数法对各元素污染程度做出评价，运用反距离加权插值法，对元素的空间分布进行分析，了解元素在各采样点属性值，最后由基于神经网络的K－means聚类分析确定元素的污染源。结果表明Cd在采样区存在强度以上的污染，Hg存在中－强度污染的采样点达20％，而As，Pb和Zn均存在中度以下污染，并且基于神经网络的K－means聚类分析不仅达到去噪的目的，在易家湾污染源分析中是合理的。
근거호남성다목표지구화학조사자료，연구료역가만지구표층토양중중금속원소As， Cd，Hg，Pb，Zn 적오염상황병심조오염원。이용지루적지수법대각원소오염정도주출평개，운용반거리가권삽치법，대원소적공간분포진행분석，료해원소재각채양점속성치，최후유기우신경망락적K－means취류분석학정원소적오염원。결과표명Cd재채양구존재강도이상적오염，Hg존재중－강도오염적채양점체20％，이As，Pb화Zn균존재중도이하오염，병차기우신경망락적K－means취류분석불부체도거조적목적，재역가만오염원분석중시합리적。
According to the data obtained from the multipurpose regional geochemical survey of Hunan province, the pollution condition and source of surface soil heavy metals , such as As, Cd, Hg, Pb and Zn in Yi-jiawan area were analyzed .Pollution level of heavy metals was accumulated by geoaccumulation index , inverse distance weighted interpolation method was used to make evaluation on elements and acquaintance values of sam -pling points , and Pollution source can be determined by K -means clustering analysis based on neural network . Conclusion can be got as this: the pollution degree of Cd outnumber intensity in the sampling area , whic ac-counts for 20%of the sampling points and Hg exits middle -intensive pollution , while the As , Pb and Zn all ex-ist pollution under the moderate pollution , and K-means clustering analysis based on neural network can not on-ly achieve the goal of denoising , but is reasonable for the pollution source analysis in Yijia wan area .