@misc{10818/36964,
year = {2010},
url = {http://hdl.handle.net/10818/36964},
abstract = {This paper presents an hybrid Neuro-Evolutive algorithm for a First-order Interval Type-2 TSK Fuzzy Logic System applied to a volatile weather forecasting case. All results are tested by statistical tests as Goldfeld-Quant, Ljung-Box, ARCH, Runs, Turning Points, Bayesian, Akaike and Hannan-Quin criteria. Some methodological aspects about a hybrid implementation among ANFIS, an Evolutive Optimizer and a First order Interval Type-2 TSK FLS are presented. The selected type-reduction algorithm is the IASCO algorithm proposed by Melgarejo in [1] since it presents better computing properties than other algorithms.},
publisher = {International Conference on Intelligent Computing},
keywords = {Fuzzy Logic System},
keywords = {Mean Square Error Criterion},
keywords = {North American Fuzzy Information Processing},
keywords = {American Fuzzy Information Processing Society},
keywords = {Volatile Time Series},
title = {A Neuro-Evolutive Interval Type-2 TSK Fuzzy System for Volatile Weather Forecasting},
doi = {10.1007/978-3-642-14922-1_19},
author = {Kalenatic, Dusko and Figueroa García, Juan Carlos and López, Cesar Amílcar},
}