Detecting recurrent patterns in time series data is an important capability. The reason is that
repeating patterns on the one hand indicate well defined processes that can be further …

The precise satellite clock bias prediction is critical in improving the positioning, navigation
and timing (PNT) service capabilities of the global navigation satellite system (GNSS). Due …

In this research we search for a functional dependence between the occurrence of forest
fires in the USA and the factors which characterize the solar activity. For this purpose we …

Forest fires that occurred in Portugal on 18 June 2017 caused several tens of human
casualties. The cause of their emergence, as well as many others that occurred in Western …

Time series event detection is related to studying methods for detecting observations in a
series with special meaning. These observations differ from the expected behavior of the …

An empirical study is performed using seasonal autoregressive fractionally integrated
moving average (SARFIMA) time series models and long short-term memory (LSTM) …

We propose a new seasonal adjustment method based on the Regularized Singular Value
Decomposition (RSVD) of the matrix obtained by reshaping the seasonal time series data …

The work examines the potential causative link between the flow of charged particles that
are coming from the Sun and hurricanes. For establishing eventual link, the method of …

Анализ краткосрочных тенденций экономической динамики требует проведения
сезонной корректировки временных рядов. На основе одного ряда строят два, один из …

The paper aims at presenting the seasonality as one of the most important elements that
influences significantly the tourist activities. The research methododology deals with the …