Spatial Outlier Detection Algorithms Based on Knowledge Discovery

This paper proposes spatial outliers detection method of studying multiple non-spatial attributes based on special objects. SOFMF algorithm is presented and its implementation has been discussed in detail in this article. Simultaneously analyze and summarize this algorithm: overcome the insufficiency of many clustering algorithms, be able to find clusters in different shapes, be non-sensitive to the input data sequence, process noise data and multi-dimensional data well, and have multi-resolution. A novel idea for spatial data clustering is proposed by the author, emphatically numerous experiments prove this idea can be applied to spatial clustering quite well.