@InProceedings{LopesSumCamCamSan:2015:PrReCh,
author = "Lopes, P. A. and Sumida, I. Y. and Camargo, H. A. and Campos
Velho, Haroldo Fraga de and Sandri, Sandra Aparecida",
affiliation = "{Universidade Federal de S{\~a}o Carlos (UFSCar)} and
{Universidade Federal de S{\~a}o Carlos (UFSCar)} and
{Universidade Federal de S{\~a}o Carlos (UFSCar)} and {Instituto
Nacional de Pesquisas Espaciais (INPE)} and {Instituto Nacional de
Pesquisas Espaciais (INPE)}",
title = "A proposal for regime change/duration classification in chaotic
systems",
booktitle = "Proceedings...",
year = "2015",
organization = "Conference of the International Fuzzy Systems Association and the
European Society for Fuzzy Logic and Technology",
keywords = "Chaotic systems, fuzzy clustering, bred vectors, Lorenz attractor,
neuro-fuzzy systems, decision trees.",
abstract = "In order to to predict regime duration in a given chaotic system,
for a set of output prototypes are available, we propose to use a
clustering technique for the definition of classes of regime
duration, which are then used by a chosen classifier. In this way,
the exact boundaries between classes are allowed to emerge from
the data, as long as prototypical values fall in distinct classes.
We investigate the use of both unsupervised and semi-supervised
fuzzy clustering techniques FCM and ssFCM, as well as the
traditional k-Means technique. To classify the data, we use
neuro-fuzzy system ANFIS and two decision trees (J48 and NBTree).
We apply the procedure on the well-known Lorenz strange attractor,
having bred vector counts as input variables.",
conference-location = "Gijon, Spain",
conference-year = "30 June - 03 July",
urlaccessdate = "27 abr. 2024"
}