An improved forecasting method of frequency density partitioning (FDP) based on fuzzy time series (FTS)

Abstract

FTS is popular in many recent years. Researchers are competing to outperform existing method by making new improvement including modifications at clustering step. Here we discuss about clustering process, i.e., partitioning based metric frequency density and firefly clustering algorithm. In the simulation, we compare the forecasting results and error value of the method with previous existing methods. The modifications give better forecasting results than previous methods indicated with smaller Root Means Errors (RMSEs) and Average Forecasting Error (AFER).