@inproceedings{e74e12d44e8447838aaf3cbad0bfc879,
title = "Memetic neuro-fuzzy system with big-bang-big-crunch optimisation",
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",
author = "Krzysztof Siminski",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2016.; 4th International Conference on Man–Machine Interactions, ICMMI 2015 ; Conference date: 06-10-2015 Through 09-10-2015",
year = "2016",
doi = "10.1007/978-3-319-23437-3\_50",
language = "English",
isbn = "9783319234366",
series = "Advances in Intelligent Systems and Computing",
publisher = "Springer Verlag",
pages = "583--592",
editor = "Tadeusz Czach{\'o}rski and Aleksandra Gruca and Agnieszka Brachman and Stanis{\l}aw Kozielski and Tadeusz Czach{\'o}rski",
booktitle = "Man–Machine Interactions - 4th International Conference on Man–Machine Interactions, ICMMI 2015",
address = "Germany",
}