Spatial Points Clustering Based on Self-organizing Neural Networks and Its Application

The principle,method and application of spatial points clustering based on self-organizing neural networks are studied.A kind of composite clustering statistic,called generalized Euclidean distance is proposed,which is calculated by both geometric and semantic characters of spatial points.Self-organizing spatial clustering based on generalized Euclidean distance can generate better result reflecting the clustering characters of spatial points.A case study to probe into data classifying,gross error detecting and homogeneous areas partitioning using self-organizing spatial clustering result is employed.