人工神经网络在识别浅覆盖区地质体中的应用  

Application of Artificial Neural Network to Distinguish Geologic Body in Shallow Overlay Area

作　　者：王大勇[1] 郝立波[1] 陆继龙[1] 

机构地区：[1]吉林大学地球探测科学与技术学院,长春130026

出　　处：《吉林大学学报（地球科学版）》2006年第S2期185-187,共3页Journal of Jilin University：Earth Science Edition

基　　金：中国地质调查局项目(200320120005)

摘　　要：利用水系沉积物资料识别浅覆盖区地质体,对于提高区域地质填图质量具有重要意义。神经网络为解决此问题提供了新的途径。依据浅覆盖区基岩和其对应的水系沉积物在化学成分上的继承关系,以内蒙古四子王旗浅覆盖区为例,阐述了运用BP神经网络模式识别地质体的原理和方法,并识别出了化学成分相近的浅覆盖层下地质体。该方法可广泛应用于浅覆盖区地质填图。It is important to enhance the quality of geologic mapping that identifying the geologic body by the stream sediment's data in shallow overlay area.Based on the artificial neural network,a new method to resolve the problem is represented.According to the inherited characteristics between bedrock and the corresponding stream sediments in shallow overlay area,taking the shallow overlay area in Siziwang County,Inner Mongolia autonomy district for example,the theory and method of BP artificial neural network mode to identify the geologic body are represented in the paper.The method identified the geologic body with the similar chemical composition under the shallow overburden layer. The method can be widely used for the geologic mapping in shallow overlay area.

关 键 词：人工神经网络 浅覆盖区 水系沉积物 地质体 

分 类 号：P632[天文地球—地质矿产勘探]