A New Hybrid Model Based on Triple Exponential Smoothing and Fuzzy Time Series for Forecasting Seasonal Time Series

DOI10.1007/978-981-15-1157-8_16zbMath1444.62108OpenAlexW3011648764MaRDI QIDQ3299995

C. Jessy John, A. J. Saleena

Publication date: 27 July 2020

Published in: Springer Proceedings in Mathematics & Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/978-981-15-1157-8_16

zbMATH Keywords

fuzzy time serieshybridtriple exponential smoothing

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Linear regression; mixed models (62J05) Applications of statistics to environmental and related topics (62P12) Applications of statistics in engineering and industry; control charts (62P30) Inference from stochastic processes and fuzziness (62M86)

Uses Software

• TDSL
• TSDL

Cites Work

• Unnamed Item
• Time series forecasting using a hybrid ARIMA and neural network model
• Forecasting Sales by Exponentially Weighted Moving Averages
• Seasonal forecasting in fuzzy time series
• The concept of a linguistic variable and its application to approximate reasoning. I
• Fuzzy time series and its models
• A fuzzy seasonal ARIMA model for forecasting
• A new approach based on the optimization of the length of intervals in fuzzy time series
• Outline of a New Approach to the Analysis of Complex Systems and Decision Processes
• Fuzzy sets
• Effective lengths of intervals to improve forecasting in fuzzy time series

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