Comparative analysis of k-means and self organizing map clustering on boiler process data

The complication exists almost in all the business applications to find out the optimal solution and envisage how the solution behaves for the changes in the equipped parameters. The engineering processing problem will have a large number of solutions out of which some are feasible and some are infeasible solutions. The aim of optimizing task is to get the best solution out of the feasible solutions set. K-means clustering method and self organizing map was implemented on boiler dataset. Results were analyzed in order to determine valuable patterns.