Genetic Algorithms-based Approaches for Clustering Time Series

2007 ◽  
pp. 3-10
Author(s):  
Roberto Baragona ◽  
Salvatore Vitrano
Keyword(s):  
Time Series ◽  
Genetic Algorithms

The Application Research on Fuzzy Theory and Genetic Algorithm

2012 ◽  
Vol 241-244 ◽  
pp. 1768-1771
Author(s):  
Xiao Qin Wu
Keyword(s):  
Time Series ◽  
Genetic Algorithms ◽  
Bp Neural Network ◽  
Financial Time Series ◽  
Fuzzy Theory ◽  
Application Research ◽  
Computing Technology ◽  
Financial Time ◽  
Better Than

Fuzzy theory is one of the newly adduced self-adaptive strategies,which is applied to dynamically adjust the parameters of genetic algorithms for the purpose of enhancing the performance.In this paper, the financial time series analysis and forecasting as the main case study to the theory of soft computing technology framework that focuses on the fuzzy logic genetic algorithms(FGA) as a method of integration. the financial time series forecasting model based on fuzzy theory and genetic algorithms was built. the ShangZheng index cards as an example. The experimental results show that FGA perform s much better than BP neural network，not only in the precision.but also in the searching speed.The hybrid algorithm has a strong feasibility and superiority.

Outliers detection in multivariate time series using genetic algorithms

2014 ◽  
Vol 132 ◽  
pp. 103-110 ◽  
Author(s):  
Domenico Cucina ◽  
Antonietta di Salvatore ◽  
Mattheos K. Protopapas
Keyword(s):  
Time Series ◽  
Genetic Algorithms ◽  
Multivariate Time Series ◽  
Outliers Detection
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