Singular spectrum analysis (SSA), starting from the second half of the 20th century, has
been a rapidly developing method of time series analysis. Since it can be called principal …

Commodity price forecasting is challenging full of volatility, uncertainty and complexity. In
this paper, a novel modeling framework is proposed to predict the market price of commodity …

Monitoring biological nutrient removal (BNR) processes at water resource recovery facilities
(WRRFs) with data-driven models is currently limited by the data limitations associated with …

This study examines the potential advantages of using Singular Spectrum Analysis (SSA) for
forecasting tourism demand. To do this it examines the performance of SSA forecasts using …

Recent advancements in signal processing and computerised methods are expected to
underpin the future progress of biomedical research and technology, particularly in …

China has adopted legislations for accelerating the non-fuel energy restructuring with
explicit targets that need to be achieved by 2020 and 2030. The joint forecasting and …

In recent years the singular spectrum analysis (SSA) technique has been further developed
and applied to many practical problems. The aim of this research is to extend and apply the …

Singular spectrum analysis (SSA) is a technique of time series analysis and forecasting. It
combines elements of classical time series analysis, multivariate statistics, multivariate …

A hybrid model is proposed for the short-term online prediction of tidal currents. The
harmonic residual analysis (HRA) model is designed to augment the numerical schemes …

Sometimes, it is of interest to single out the fluctuations associated to a given frequency. We
propose a new variant of SSA, Circulant SSA (CiSSA), that allows to extract the signal …