The article introduces a new method for clustering data called Neighborhood Density based Clustering with Agglomerative Fuzzy K-Means Algorithm. The goal is to improve the initial selection of cluster centers by identifying high-density neighborhoods in the data. This method helps create more accurate clusters by merging these initial centers using the Agglomerative Fuzzy K-Means algorithm. The researchers found that this approach automatically determines the correct number of clusters and produces more consistent and accurate clustering results compared to traditional methods.