An Evolutionary Approach for Modeling Time Series

Created by W.Langdon from gp-bibliography.bib Revision:1.7630

@InProceedings{Bautu:2008:SYNASC,

• author = "Elena Bautu and Andrei Bautu and Henri Luchian",
• title = "An Evolutionary Approach for Modeling Time Series",
• booktitle = "10th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing, SYNASC '08",
• year = "2008",
• month = sep,
• pages = "507--513",
• keywords = "genetic algorithms, genetic programming, change point detection, data generation process, evolutionary approach, genetic operator, time series modeling, time series",
• DOI = "doi:10.1109/SYNASC.2008.63",
• abstract = "Change points in time series appear due to variations in the data generation process. We consider the problem of modeling time series generated by dynamic processes, and we focus on finding the change points using a specially tailored genetic algorithm. The algorithm employs a new representation, described in detail in the paper. Suitable genetic operators are also defined and explained. The results obtained on computer generated time series provide evidence that the approach can be used for change point detection, and has good potential for time series modeling.",
• notes = "Also known as \cite{5204862}",

}

Genetic Programming entries for Elena Bautu Andrei Bautu Henri Luchian

Citations