IWINAC2017: Sessions

Chairperson: Jose C. Riquelme Santos
Co-chairperson: Francisco Martinez Alvarez

Time series can be found in almost all disciplines nowadays, turning their efficient analysis is of utmost relevance for the scientific community. Thus, this session pays attention to the extraction of useful knowledge from time series, using techniques inspired on natural and artificial computing. The analysis of very large time series, given its relevance in the emergent context of big data, is particularly encouraged.

Topics of interest for the special session, always in the context of natural and artificial computing, include but are not limited to:

Machine learning applied to time series, including classification, clustering and forecasting.

New approaches for big time series data classification and forecasting.

Efficient computing for multisensor, multisource and multiprocess information fusion.

Hybrid systems for time series analysis.

Ensemble based approaches for time series analysis.

Natural and artificial computing in time series with outliers.

IWINAC2017: Pre-Organized Session:

S11. Natural and artificial computing for time series analysis (NAC-TS)