Dealing with temporal and spatial correlations to classify outliers in geophysical data streams

DOI10.1016/J.INS.2013.12.009zbMath1355.68222DBLPjournals/isci/AppiceGMC14OpenAlexW2091134873WikidataQ57568234 ScholiaQ57568234MaRDI QIDQ508690

Annalisa Appice, Anna Ciampi, Donato Malerba, Pietro Guccione

Publication date: 7 February 2017

Published in: Information Sciences (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.ins.2013.12.009

zbMATH Keywords

time series forecastingtemporal correlationspatial correlationoutlier detection and classification

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Classification and discrimination; cluster analysis (statistical aspects) (62H30) Measures of association (correlation, canonical correlation, etc.) (62H20) Learning and adaptive systems in artificial intelligence (68T05) Computational methods for problems pertaining to geophysics (86-08)

Related Items (3)

Transductive hyperspectral image classification: toward integrating spectral and relational features via an iterative ensemble system ⋮ Active learning via collective inference in network regression problems ⋮ Using multiple time series analysis for geosensor data forecasting

Uses Software

• StreamKrimp

Cites Work

• Knowledge Discovery from Data Streams
• Business Intelligence
• Advances in Artificial Intelligence – SBIA 2004
• Fault detection and diagnosis in industrial systems

This page was built for publication: Dealing with temporal and spatial correlations to classify outliers in geophysical data streams