%0 Journal Article %A JIANG Yu %A LONG Chaoqi %A XIE Yu %T Improved wavelet clustering algorithm based on peak grid %D 2021 %R 10.11772/j.issn.1001-9081.2020071042 %J Journal of Computer Applications %P 1122-1127 %V 41 %N 4 %X Aiming at the difference between the clustering effects of wavelet clustering algorithm under different grid division scales, an improved method based on peak grid was proposed. The algorithm mainly aimed at improving the detection method of connected regions in wavelet clustering. First, the spatial grids after wavelet transform were sorted according to the grid values; then, the breadth-first-search method was used to traverse each spatial grid to detect the peak connected regions in the data after wavelet transform; finally, the connected regions were marked and mapped to the original data space to obtain the clustering result. Experimental results of 8 synthetic datasets(4 convex datasets and 4 non-convex datasets) and 2 real datasets in the UCI database showed that the improved algorithm had good performance at low grid division scales, and compared with the original wavelet clustering algorithm, this algorithm had the requirement for grid division scale reduced by 25% to 60%, and the clustering time reduced by 14% under the same clustering effect. %U http://www.joca.cn/EN/10.11772/j.issn.1001-9081.2020071042