Particle swarm optimization of ensemble neural networks with fuzzy aggregation for time series prediction of the Mexican Stock Exchange

DOI10.1016/j.ins.2014.05.006zbMath1359.62464OpenAlexW2080937097WikidataQ58488461 ScholiaQ58488461MaRDI QIDQ507625

Oscar Castillo, Patricia Melin, Martha Pulido

Publication date: 7 February 2017

Published in: Information Sciences (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.ins.2014.05.006

zbMATH Keywords

time series predictionparticle swarm optimizationensemble neural network

Mathematics Subject Classification ID

Inference from stochastic processes and prediction (62M20) Applications of statistics to actuarial sciences and financial mathematics (62P05) Approximation methods and heuristics in mathematical programming (90C59)

Related Items (4)

Stochastic stability analysis of composite dynamic system for particle swarm optimization ⋮ Kernel sparse representation for time series classification ⋮ Prepositioning emergency earthquake response supplies: a new multi-objective particle swarm optimization algorithm ⋮ Finding sums of powers using physical arguments

Uses Software

• itsmr

Cites Work

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• A simple method of forecasting based on fuzzy time series
• Predicting a chaotic time series using a fuzzy neural network
• Applications of type-2 fuzzy logic systems to forecasting of time-series
• Practical Optimization
• Introduction to Time Series and Forecasting
• Operations on type-2 fuzzy sets
• Effective lengths of intervals to improve forecasting in fuzzy time series

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