Paper Info
Title
Automatic Generation of Type-1 and Interval Type-2 Membership Functions for Prediction of Time Series Data.
Abstract
use of type-1 or type-2 membership functions in fuzzy systems offers a wide range of research opportunities. In this aspect, there are neither formal recommendations, methods that can help to decide which type of membership function should be chosen nor has the process of generating these membership functions been formalized. Against this background, this paper describes a study comparing the results of employing both a Genetic Algorithm and a Simulated Annealing for automatic generation of type-1 and interval type-2 membership functions. The paper also describes tests with different degrees of uncertainty inherent both to the input data and the fuzzy system rules. Experiments were conducted to predict the Mackey-Glass time series and the results were verified using statistical tests. The data obtained from statistical analysis can be used to determine which type of membership function is most appropriate for the problem.
Year
DOI
Venue
2016
10.1007/978-3-319-47955-2_29
ADVANCES IN ARTIFICIAL INTELLIGENCE - IBERAMIA 2016
Keywords
Field
DocType
Genetic algorithms,Interval Type-2 fuzzy sets,Membership functions,Prediction of time series data,Simulated annealing
Simulated annealing,Time series,Data mining,Computer science,Artificial intelligence,Fuzzy control system,Membership function,Machine learning,Genetic algorithm,Statistical hypothesis testing,Statistical analysis
Conference
Volume
ISSN
Citations 
10022
0302-9743
0
PageRank 
References 
Authors
0.34
22
3
Name
Order
Citations
PageRank
andr ia alves dos santos schwaab100.68
Silvia Nassar286.52
Paulo J. de Freitas Filho36011.21