Applications of Self-organizing Feature Map Networks to Chart Development of Complex Hydrocarbon Formation Recognition
Wen Huanming,Xiao Cixun, Li Wei, et al..
The self-organizing feature map network is a kind of nonlinear method that is mainly applied to the clustering analyses of samples without prior knowledge.Here is a different methodology from the old one. At first, clustering analyses for the learning samples with prior knowledge are made through the self-organizing feature map network. And then the learning samples are projected to a 2D topological space (planar map). Finally, the recognition standards are defined by means of the different distribution area responding to the type of samples in the 2D topological space.The method has more advantages than the crossplot in the chart development of complex hydrocarbon formation recognition. The good application has been available in the field's work.
【CateGory Index】： P631.8