Subsequence similarity matching in time series databases is an important research area for many applications. This paper presents a new approximate approach for automatic online s...
Innovative scientific applications and emerging dense data sources are creating a data deluge for highend computing systems. Processing such large input data typically involves cop...
Henry M. Monti, Ali Raza Butt, Sudharshan S. Vazhk...
Recurrent Self-Organizing Map (RSOM) is studied in three di erent time series prediction cases. RSOM is used to cluster the series into local data sets, for which corresponding lo...
Timo Koskela, Markus Varsta, Jukka Heikkonen, Kimm...
Evolving Takagi Sugeno (eTS) models are optimised for use in applications with high sampling rates. This mode of use produces excellent prediction results very quickly and with lo...
Abstract. This paper presents k-NN as an approximator for time series prediction problems. The main advantage of this approximator is its simplicity. Despite the simplicity, k-NN c...