Integrating Cluster Analysis to the ARIMA Model for Forecasting Geosensor Data

Torna indietro

Abstract

Clustering geosensor data is a problem that has recently attracted a large amount of research. In this paper, we focus on clustering geophysical time series data measured by a geo-sensor network. Clusters are built by accounting for both spatial and temporal information of data. We use clusters to produce globally meaningful information from time series obtained by individual sensors. The cluster information is integrated to the ARIMA model, in order to yield accurate forecasting results. Experiments investigate the trade-off between accuracy and efficiency of the proposed algorithm.

Autore Pugliese

Tutti gli autori

  • APPICE A.;MALERBA D.

Titolo volume/Rivista

Non Disponibile

Anno di pubblicazione

2014

ISSN

0302-9743

ISBN

978-3-319-08325-4

Numero di citazioni Wos

Nessuna citazione

Ultimo Aggiornamento Citazioni

Non Disponibile

Numero di citazioni Scopus

9

Ultimo Aggiornamento Citazioni

Non Disponibile

Settori ERC

Non Disponibile

Codici ASJC

Non Disponibile