An ARMA type fuzzy time series forecasting method based on particle swarm optimization

DOI10.1155/2013/935815zbMath1299.62088OpenAlexW2133010150WikidataQ59029740 ScholiaQ59029740MaRDI QIDQ474751

Erol Eğrioğlu, Cem Kocak, Ufuk Yolcu, Cagdas Hakan Aladag

Publication date: 24 November 2014

Published in: Mathematical Problems in Engineering (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1155/2013/935815

Mathematics Subject Classification ID

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 (5)

A new high order fuzzy ARMA time series forecasting method by using neural networks to define fuzzy relations ⋮ A hybrid fuzzy time series approach based on fuzzy clustering and artificial neural network with single multiplicative neuron model ⋮ First-order ARMA type fuzzy time series method based on fuzzy logic relation tables ⋮ Uncertain time series analysis with imprecise observations ⋮ Forecasting based on high-order fuzzy-fluctuation trends and particle swarm optimization machine learning

Uses Software

• longmemo

Cites Work

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