Developing an Enterprise Management System using Weighted K-means Clustering Algorithm

Recently, enterprises are extremely spread as well as cheap throughout the globe. Enterprise Management System (EMS) can assist enterprise managers in enhancing the efficiency of the work as well as minimizing the work load. In recent years, the cluster analysis is generally utilized data analysis approaches, and K-means is famous as well as majorly utilized clustering algorithms. Due to the performance of clustering, it is majorly utilized in enterprises. This research proposed the Weighted K-means clustering approach of an EMS. The proposed approach had accessed the business to rapidly solved the problem of dependencies, enhance the data in every field, complement required resources as well as endorse development. The proposed method creates it simple to determine the system faintness as well as supplies the secure guarantee to the sustainable enterprises development. This method aims to rationally utilize the limited business scheduling resources in the production business. MATLAB simulates a superior configuration scheme, which validates the science and efficacy of the method studied in this research.