Open AccessAn improved forecasting method of frequency density partitioning (FDP) based on fuzzy time series (FTS)
Author(s) -
Bambang Irawanto,
R. W. Ningrum,
Bayu Surarso,
Farikhin
Publication year - 2019
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1321/2/022082
Subject(s) - cluster analysis , computer science , series (stratigraphy) , metric (unit) , fuzzy clustering , firefly algorithm , data mining , algorithm , process (computing) , artificial intelligence , engineering , paleontology , operations management , particle swarm optimization , biology , operating system
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).