Cita:
Andre Ponce de Leon F. de Carvalho. et al. (eds.) (2010) Distributed Computing and Artificial Intelligence: 7th International Conference, (Advances in Intelligent and Soft Computing, 79) Springer, pp. 267- 274.
Agradecimientos:
This work was supported in part by Projects CICYT TIN2008-06742-C02-02/TSI, CICYT TEC2008-06732-C02-02/TEC, CAM CONTEXTS (S2009/TIC-1485) and DPS2008-07029-C02-02.
Serie/Num.:
Advances in Intelligent and Soft Computing 79
Proyecto:
Comunidad de Madrid. S2009/TIC-1485/CONTEXTS
Palabras clave:
Segmentation Processes
,
Multiobjetive Optimization Problem
,
Piecewise Linear Representation
Actual time series exhibit huge amounts of data which require an unaffordable computational load to be processed, leading to approximate representations to aid these processes. Segmentation processes deal with this issue dividing time series into a certain numActual time series exhibit huge amounts of data which require an unaffordable computational load to be processed, leading to approximate representations to aid these processes. Segmentation processes deal with this issue dividing time series into a certain number of segments and approximating those segments with a basic function. Among the most extended segmentation approaches, piecewise linear representation is highlighted due to its simplicity. This work presents an approach based on the formalization of the segmentation process as a multiobjetive optimization problem and the resolution of that problem with an evolutionary algorithm.[+][-]
Nota:
Proceedings of: Forth International Workshop on User-Centric Technologies and applications (CONTEXTS 2010). Valencia, September 7-10, 2010
