化探数据具有非线性、随机性等特点,而传统地球化学元素组合异常的确定方法虽然考虑了变量的随机性,但却忽视了其非线性,这无疑会造成重要信息的丢失.而独立分量分析不仅要求各分量二阶不相关,同时还要求高阶统计量不相关.这使其在发掘数据间的高阶相关信息方面更具优势.这里以西藏某铜金矿1∶10 000土壤化探数据为案例,对组合异常进行了分析与评价,尝试探索非线性理论在地球化学数据处理上的新方法.%Geochemical survey data is non-linear and randomness. Although the traditional method of identifying geochemical element associations a-nomaly takes the randomness into account, it ignores the non-linear of original data. Obviously, it has to loose important information. Independent Component Analysis, however, not only requires second-order statistics of each component to satisfy Non-Gaussian distribution, but need to high-order statistics are non-correlation. It seems that this feature gives ICA a big advantage over the traditional one for digging high correlation information. This article will launch the analysis and evaluation of multi-element association anomaly by an area in Tibet 1:10,000 metrical soil data. Also, we attempt to explore new method of processing geochemical data based on non-linear theory.
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