In today’s day and age, a mobile phone has become basic requirement needed for anyone to thrive. With the cellular traffic demand increasing so dramatically, it is now necessary accurately predict user in networks, improve performance terms of resource allocation utilization. Since learning prediction classical appealing field, which still yields many meaningful results, there been an interest ...

Transformer architecture has widespread applications, particularly in Natural Language Processing and computer vision. Recently Transformers have been employed various aspects of time-series analysis. This tutorial provides an overview the architecture, its a collection examples from recent research papers We delve into explanation core components Transformer, including self-attention mechanism...

This paper presents a method to summarize massive spacecraft telemetry data by extracting significant event and change patterns in the lowlevel time-series data. This method first transforms the numerical timeseries into a symbol sequence by a clustering technique using DTW distance measure, then detects event patterns and change points in the sequence. We demonstrate that our method can succes...

We propose a general interpretation for long-range correlation effects in the activity and volatility of financial markets. This interpretation is based on the fact that the choice between ‘active’ and ‘inactive’ strategies is subordinated to random-walk like processes. We numerically demonstrate our scenario in the framework of simplified market models, such as the Minority Game model with an ...

in the management of river basins, prediction of river water quality is essential to maintain water quality within standard limits. this study performed a time-series analysis of the prediction of chlorine concentration and electrical conductivity time series data for the period of 1991-2005 from sefidrood river in northern iran. the seasonal prediction of chlorine and electrical conductivity t...

In the last few decades, huge amounts of climate data have been gathered and stored by several institutions. The analysis of these data has become an important task due to worldwide climate changes and the consequent social and economic effects. In this work, we propose an approach to analyzing multiple climate time series in order to identify intrinsic temporal patterns and trend changes. By d...

The research scope of grey relational analysis has not been developed in recent years, and the exiting GRA models are all based on three perspectives, including distance perspective, slope perspective, and area perspective. Under this situation, a novel model called grey relational analysis based on angle perspective (GRAAP) was developed in this paper for the first time, and this model can exp...