Traditional DBSCAN algorithm usually set the threshold(min

) depending on empirical value

and merely fit for single-density data sets

in allusion to the shortage

the article puts forward a new adaptive DBSCAN algorithm which based on Gaussian distribution and can be used to multi-density data sets.The new algorithm can generate proper threshold according to the data set characteristics.Firstly

to get the min accornding to the max CEI value.Then

to confirm the number of according to the curve density level

so that to get data by the Gaussian distribution law.At last

to make clustering for the data set with the min and value.Also

to apply the new algorithm and the traditional DBSCAN algorithm to single-density and multi-density data sets

the results show that the new algorithm is more efficient.