@book{eb152175322f46b49c21e64d4d869c56,
title = "MAPS: A method for identifying and predicting aberrant behaviour in time series",
abstract = "We present a method for inducing a set of rules from time series data, which is originated monitoring process. The proposed method is called MAPS (Mining Aberrant Patterns in Sequences) and it may be used in decision support or in control to identify faulty system states. It consists of four parts: training, identification, mining and prediction. In order to improve the flexibility of the event identification, we employ fuzzy sets and propose a method that extracts membership functions from statistical measures of the time series. The proposed approach integrates fuzzy logic and mining in a seamless ways. Some of the existing mining algorithms have been modified to accommodate the need of discovering fuzzy event pattern.",
keywords = "modelling behaviour, rule extraction, mining even structures Mining Aberrant Pattern in Sequences",
author = "Evangelos Kotsakis and Antoni Wolski",
year = "2000",
language = "English",
series = "VTT Information Technology. Research Report",
publisher = "VTT Technical Research Centre of Finland",
number = "TTE1-2000-42",
address = "Finland",
}