An Immense Approach of High Order Fuzzy Time Series Forecasting of Household Consumption Expenditures with High Precision-Reference-Cited by-同舟云学术

An Immense Approach of High Order Fuzzy Time Series Forecasting of Household Consumption Expenditures with High Precision

Published:2024-06-01 Issue:1 Volume:29 Page:1-7
ISSN:2255-8691
Container-title:Applied Computer Systems
language:en
Short-container-title:

Author:

Burney Syed Muhammad Aqil¹^ORCID,Khan Muhammad Shahbaz²^ORCID,Alim Affan³^ORCID,Efendi Riswan⁴^ORCID

Affiliation:

1. College of Computer Science and Information Systems, Institute of Business Management , Karachi , Pakistan ; Department of Computer Science , University of Karachi , Pakistan

2. College of Humanities and Sciences, Karachi Institute of Economics and Technology , Pakistan

3. Computer Science Department , IQRA University , Karachi , Pakistan

4. Faculty of Science and Technology, UIN Sultan Syarif Kasim Riau , Indonesia

Abstract

Abstract Fuzzy Time Series (Fts) models are experiencing an increase in popularity due to their effectiveness in forecasting and modelling diverse and intricate time series data sets. Essentially these models use membership functions and fuzzy logic relation functions to produce predicted outputs through a defuzzification process. In this study, we suggested using a Second Order Type-1 fts (S-O T-1 F-T-S) forecasting model for the analysis of time series data sets. The suggested method was compared to the state-of-theart First Order Type 1 Fts method. The suggested approach demonstrated superior performance compared to the First Order Type 1 Fts method when applied to household consumption data from the Magene Regency in Indonesia, as measured by absolute percentage error rate (APER).

Publisher

Walter de Gruyter GmbH

Link

https://www.sciendo.com/pdf/10.2478/acss-2024-0001

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