title: Konzeptioneller Ansatz einer Fehlerprädiktionsumgebung
creator: Größl, Martin
description: In this thesis a failure prediction environment based on selected methods of statistics, machine learning and data mining was developed. For the system behavior representation of an observed information system mathematical models,such as Bayesian networks and Markov chains, were generated. These models were analyzed using a probabilistic model-checking for both the process evolution (path) into a fault condition as well as the time duration until the occurrence  of this possible fault.  Furthermore, based on a Kalman filter an approach for identification of anomalies and / or misbehavior in data streams was developed. This also includes a system identification part, which derives the models from measurement data.  These models form the basis for the misbehavior detection.
date: 2017
type: Dissertation
type: info:eu-repo/semantics/doctoralThesis
type: NonPeerReviewed
format: application/pdf
identifier: https://archiv.ub.uni-heidelberg.de/volltextserverhttps://archiv.ub.uni-heidelberg.de/volltextserver/23714/1/Phd_Thesis_Martin_Groessl_UNI.pdf
identifier: DOI:10.11588/heidok.00023714
identifier: urn:nbn:de:bsz:16-heidok-237144
identifier:   Größl, Martin  (2017) Konzeptioneller Ansatz einer Fehlerprädiktionsumgebung.  [Dissertation]     
relation: https://archiv.ub.uni-heidelberg.de/volltextserver/23714/
rights: info:eu-repo/semantics/openAccess
rights: http://archiv.ub.uni-heidelberg.de/volltextserver/help/license_urhg.html
language: ger