Path: Top -> Journal -> Telkomnika -> 2018 -> Vol. 16, No. 4, August

A Novel Forecasting Based on Automatic-optimized Fuzzy Time Series

Journal from gdlhub / 2018-07-26 11:17:47
Oleh : Yusuf Priyo Anggodo, Wayan Firdaus Mahmudy, Telkomnika
Dibuat : 2018-07-26, dengan 1 file

Keyword : Fuzzy Logical Relationship; Two-Factor High-Order Fuzzy-Trend; Logical Relationship Groups; Automatic-Optimized; Similarity Measures
Url : http://journal.uad.ac.id/index.php/TELKOMNIKA/article/view/8430
Sumber pengambilan dokumen : WEB

In this paper, we propose a new method for forecasting based on automatic-optimized fuzzy time series to forecast Indonesia Inflation Rate (IIR). First, we propose the forecasting model of two-factor high-order fuzzy-trend logical relationships groups (THFLGs) for predicting the IIR. Second, we propose the interval optimization using automatic clustering and particle swarm optimization (ACPSO) to optimize the interval of main factor IIR and secondary factor SF, where SF = {Customer Price Index (CPI), the Bank of Indonesia (BI) Rate, Rupiah Indonesia /US Dollar (IDR/USD) Exchange rate, Money Supply}. The proposed method gets lower root mean square error (RMSE) than previous methods.

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PropertiNilai Properti
ID Publishergdlhub
OrganisasiTelkomnika
Nama KontakHerti Yani, S.Kom
AlamatJln. Jenderal Sudirman
KotaJambi
DaerahJambi
NegaraIndonesia
Telepon0741-35095
Fax0741-35093
E-mail Administratorelibrarystikom@gmail.com
E-mail CKOelibrarystikom@gmail.com

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