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Detection of anomalies and extreme events in multidimensional data streams.

Grant number: 11/15829-5
Support type:Scholarships in Brazil - Master
Effective date (Start): March 01, 2012
Effective date (End): February 28, 2014
Field of knowledge:Physical Sciences and Mathematics - Computer Science - Computing Methodologies and Techniques
Principal researcher:Elaine Parros Machado de Sousa
Grantee:Santiago Augusto Nunes
Home Institution: Instituto de Ciências Matemáticas e de Computação (ICMC). Universidade de São Paulo (USP). São Carlos , SP, Brazil

Abstract

Data streams are usually characterized by large amounts of data generated in continuous, potentially infinite, synchronous or asynchronous processes, in applications such as: meteorological systems, industrial processes, vehicle monitoring systems, financial transactions, sensor networks, among others. Moreover, the behavior of the data tends to change significantly over time, defining evolving data streams. These changes may mean temporary events (such as anomalies or extreme events) or relevant changes in the process of generating the stream (i.e., changes in data distribution). Detecting these behavior variations, especially anomalies and extreme events, is relevant for some types of applications, such as monitoring climate extremes in research on Agrometeorology. In this context, this project aims to develop a technique for identifying anomalies and extreme events in multidimensional data streams, based on the detection of spatio-temporal behavior changes. Our approach is based on concepts from the fractal theory, applied to analyze temporal behavior. Furthermore, we aim to apply the developed technique to agro-meteorological data, in order to identify extreme climate events and the impact of these events on coffee growing areas in southeastern Brazil. Therefore, this work can potentially result in contributions to the data mining area and support research on Agrometeorology.

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Academic Publications
(References retrieved automatically from State of São Paulo Research Institutions)
NUNES, Santiago Augusto. Spatio-temporal analysis in multidimensional data streams. 2015. Master's Dissertation - Universidade de São Paulo (USP). Instituto de Ciências Matemáticas e de Computação (ICMC/SB) São Carlos.

Please report errors in scientific publications list by writing to: cdi@fapesp.br.