摘要
针对物化探综合异常反映出的高维空间复杂结构和相互之间复杂关系等现象,通过对多维信息的降维处理,提取综合异常的特征参量,建立了表述物化探综合异常的初始模型。以模糊数学为手段,对已知区的综合异常进行模糊分类评价,建立了物化探综合异常评价模型。利用人工神经网络,通过学习建立识别系统,对未知综合异常进行识别,完成了对复杂物化探综合异常的评价。实例表明,该评价方法是合理可行的。
For such phenomena of the complex structure in the high-dimensions space and its relationship reflected the comprehensive anomalies of geophysics and geochemistry exploration,the initial model is built which describe the comprehensive anomalies of geophysics and geochemistry exploration with dropping down dimensions for the multi-dimentional information and extracting the characteristic parameters of comprehensive anomalies;According to the assessment of the fuzzy cluster method for the comprehensive anomalies in confirmed area,Using the fuzzy clustering method to build the model which can evaluate the anomaly.By learning to build the recognition system based on the artificial neural network theory,we complete the evaluation of the complex comprehensive anomalies of geophysics and geochemistry exploration after pattern recognize for the unknown comprehensive anomalies.The examples show that the method is reasonable and feasible.
出处
《物探化探计算技术》
CAS
CSCD
2010年第6期629-635,共7页
Computing Techniques For Geophysical and Geochemical Exploration
关键词
综合异常
特征参量
模糊聚类
人工神经网络
模式识别
comprehensive anomalies
characteristic parameters
fuzzy clustering
artificial neural network
pattern recognize
