Memetic Neuro-Fuzzy System with Big-Bang-Big-Crunch Optimisation

Conference paper

DOI: 10.1007/978-3-319-23437-3_50

Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 391)
Cite this paper as:
Siminski K. (2016) Memetic Neuro-Fuzzy System with Big-Bang-Big-Crunch Optimisation. In: Gruca A., Brachman A., Kozielski S., Czachórski T. (eds) Man–Machine Interactions 4. Advances in Intelligent Systems and Computing, vol 391. Springer, Cham

Abstract

The paper presents a memetic fuzzy inference system based on Big Bang Big Crunch (evolutionary optimisation) and gradient descent (local search) techniques. Tuning parameters of the fuzzy system with evolutionary optimisation failed to be successful, but application of both evolutionary and local optimisation achieved lower error rates than reference system (that uses only gradient descent optimisation). The results of experiments have been statistically verified.

Keywords

Approximate inversion Imputation Incomplete data Neuro-fuzzy system 

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.Institute of InformaticsSilesian University of TechnologyGliwicePoland

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