Surrogate data methods have been widely applied to produce synthetic data, while maintaining the same statistical properties as the original. By using such methods, one can analyze certain properties of time series. In ...

Time-series forecasting is an important field of machine learning and is fundamental in analyzing trends based on historical data from various sources. In this paper, a fuzzy ARTMAP neural network for time-series forecasting ...

The current ability to produce massive amounts of data and the impossibility in storing it motivated the development of data stream mining strategies. Despite the proposal of many techniques, this research area still lacks ...

Topology is the branch of mathematics that studies how objects relate to one another for their qualitative structural properties, such as connectivity and shape. In this paper, we present an approach for data clustering ...

The Spanish Antarctic Station Juan Carlos I has been registering surface air temperatures with the frequency of one reading per ten minutes since the austral summer 1987-88. Although this data set contains valuable information ...

The support of time series similarity searches might be crucial in phenology studies, in which long-term time series analysis based on the identification of similar and different phenological patterns shared by individuals ...

The support of time series similarity searches might be crucial in phenology studies, in which long-term time series analysis based on the identification of similar and different phenological patterns shared by individuals ...