A new time-invariant fuzzy time series forecasting method based on genetic algorithm

DOI10.1155/2012/785709zbMath1252.62092OpenAlexW2052369115WikidataQ58698173 ScholiaQ58698173MaRDI QIDQ446402

Erol Eğrioğlu

Publication date: 6 September 2012

Published in: Advances in Fuzzy Systems (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1155/2012/785709

Mathematics Subject Classification ID

Inference from stochastic processes and prediction (62M20) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Approximation methods and heuristics in mathematical programming (90C59) Inference from stochastic processes and fuzziness (62M86)

Related Items (3)

A new method for short multivariate fuzzy time series based on genetic algorithm and fuzzy clustering ⋮ An ARMA type fuzzy time series forecasting method based on particle swarm optimization ⋮ A unified approach to asymptotic behaviors for the autoregressive model with fuzzy data

Cites Work

• Fuzzy time series and its models
• A FCM-based deterministic forecasting model for fuzzy time series
• FORECASTING ENROLLMENTS BASED ON HIGH-ORDER FUZZY TIME SERIES
• Forecasting enrollments using high-order fuzzy time series and genetic algorithms
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