Huang, Y.L., 2020. Financial investment recommendation in coastal areas based on improved clustering algorithm. In: Al-Tarawneh, O. and Megahed, A. (eds.), Recent Developments of Port, Marine, and Ocean Engineering. Journal of Coastal Research, Special Issue No. 110, pp. 215–218. Coconut Creek (Florida), ISSN 0749-0208.
Based on the full analysis of the advantages and disadvantages of the traditional K - means and BIRCH clustering algorithms, an improved incremental clustering algorithm based on the core tree is proposed. The optimal global parameters Eps and MinPts are adaptively calculated according to the KNN distribution and mathematical statistics to avoid manual intervention in the clustering process so as to realize the full automation of the clustering process. By improving the seed selection method for regional query, no missing operation is needed to effectively improve the efficiency of clustering. The algorithm can helps financial users to make reasonable financial investment strategies in coastal areas, to a certain extent, reduce the financial investment risk, with strong practical significance.