Using an improved spatial clustering model for evaluation of industry agglomeration

Abstract

In the past researches, industrial agglomeration mainly focused on single or particular industry and less on spatial industrial structure and mutual relations. In addition, industrial cluster indeed benefits industry development. To fully control the status and characteristics of district industrial, cluster can facilitate to improve the competitive ascendancy of district industry. The related researches on industrial spatial cluster were of great significance for setting up industrial policies and promoting district economic development. In this study, an improved model that combines DBSCAN and SOM was developed for analyzing industrial cluster. Different from distance-based algorithm for industrial cluster, the proposed model can calculate spatial characteristics between firms based on DBSCAN algorithm and evaluate the similarity of attributes between firms based on SOM model. The demonstrative data sets, 25 random sampling of firms around Taichung County in central Taiwan, were analyzed for verifying the practicability of the proposed model. The analyzed results indicate that the proposed model is suitable for evaluating spatial industrial cluster. This research benefits on regional development decision-making for local government.