Log in

Relevant bibliographies by topics / Time series outlier detection / Dissertations / Theses

To see the other types of publications on this topic, follow the link: Time series outlier detection.

Dissertations / Theses on the topic 'Time series outlier detection'

Author: Grafiati

Published: 28 June 2021

Last updated: 29 July 2025

Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles

Select a source type:

Consult the top 50 dissertations / theses for your research on the topic 'Time series outlier detection.'

Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.

You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.

Browse dissertations / theses on a wide variety of disciplines and organise your bibliography correctly.

1

Sedman, Robin. "Online Outlier Detection in Financial Time Series." Thesis, KTH, Matematisk statistik, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-228069.

Full text

Abstract:

In this Master’s thesis, diﬀerent models for outlier detection in ﬁnancial time series are examined. The ﬁnancial time series are price series such as index prices or asset prices. Outliers are, in this thesis, deﬁned as extreme and false points, but this deﬁnition is also investigated and revised. Two diﬀerent time series models are examined: an autoregressive (AR) and a generalized autoregressive conditional heteroskedastic (GARCH) time series model, as well as one test statistic method based on the GARCH model. Additionally, a nonparametric model is examined, which utilizes kernel density e

APA, Harvard, Vancouver, ISO, and other styles

2

Wang, Dan Tong. "Outlier detection with data stream mining approach in high-dimenional time series data." Thesis, University of Macau, 2017. http://umaclib3.umac.mo/record=b3691091.

Full text

APA, Harvard, Vancouver, ISO, and other styles

3

Bergamelli, Michele. "Structural breaks and outliers detection in time-series econometrics : methods and applications." Thesis, City University London, 2015. http://openaccess.city.ac.uk/14868/.

Full text

Abstract:

This thesis contributes to the econometric literature on structural breaks analysis and outliers detection in parametric linear models. The focus is on the development of new econometric tools as well as on the analysis of novel but largely unexplored approaches. The econometric methods under analysis are illustrated using macroeconomic and financial relationships. The thesis is organised in three main chapters. In Chapter 2, we consider two novel methods to detect multiple structural breaks affecting the deterministic component of a linear system. The first is an extension of the dummy satura

APA, Harvard, Vancouver, ISO, and other styles

4

Eghbalian, Amirmohammad. "Data mining techniques for modeling the operating behaviors of smart building control valve systems." Thesis, Blekinge Tekniska Högskola, Institutionen för datavetenskap, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-20102.

Full text

Abstract:

Background. One of the challenges about smart control valves system is processing and analyzing sensors data to extract useful information. These types of information can be used to detect the deviating behaviors which can be an indication of faults and issues in the system. Outlier detection is a process in which we try to find these deviating behaviors that occur in the system.Objectives. First, perform a literature review to get an insight about the machine learning (ML) and data mining (DM) techniques that can be applied to extract patternfrom time-series data. Next, model the operating be

APA, Harvard, Vancouver, ISO, and other styles

5

Slávik, Ľuboš. "Dynamická faktorová analýza časových řad." Master's thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2021. http://www.nusl.cz/ntk/nusl-445469.

Full text

Abstract:

Táto diplomová práca sa zaoberá novým prístupom k zhlukovaniu časových rád na základe dynamického faktorového modelu. Dynamický faktorový model je technika redukujúca dimenziu a rozširuje klasickú faktorovú analýzu o požiadavku autokorelačnej štruktúry latentných faktorov. Parametre modelu sa odhadujú pomocou EM algoritmu za použitia Kalmanovho filtra a vyhladzovača a taktiež sú aplikované nevyhnutné podmienky na model, aby sa stal identifikovateľným. Po tom, ako je v práci predstavený teoretický koncept prístupu, dynamický faktorový model je aplikovaný na skutočné pozorované časové rady a prá

APA, Harvard, Vancouver, ISO, and other styles

6

Allab, Nedjmeddine. "Détection d'anomalies et de ruptures dans les séries temporelles. Applications à la gestion de production de l'électricité." Thesis, Paris 6, 2016. http://www.theses.fr/2016PA066658.

Full text

Abstract:

Continental est l'outil de référence utilisé par EDF pour la gestion d'électricité à long terme. il permet d'élaborer la stratégie d'exploitation du parc constitué de centrales réparties sur toute l'europe. l'outil simule sur chaque zone et chaque scénario plusieurs variables telles que la demande d'électricité, la quantité générée ainsi que les coûts associés. nos travaux de thèse ont pour objectif de fournir des méthodes d'analyse de ces données de production afin de faciliter leur étude et leur synthèse. nous récoltons un ensemble de problématiques auprès des utilisateurs de continental que

APA, Harvard, Vancouver, ISO, and other styles

7

Ribeiro, Joana Patrícia Bordonhos. "Outlier identification in multivariate time series." Master's thesis, Universidade de Aveiro, 2017. http://hdl.handle.net/10773/22200.

Full text

Abstract:

Mestrado em Matemática e Aplicações<br>Com o desenvolvimento tecnológico, existe uma cada vez maior disponibilidade de dados. Geralmente representativos de situações do dia-a-dia, a existência de grandes quantidades de informação tem o seu interesse quando permite a extração de valor para o mercado. Além disso, surge importância em analisar não só os valores disponíveis mas também a sua associação com o tempo. A existência de valores anormais é inevitável. Geralmente denotados como outliers, a procura por estes valores é realizada comummente com o intuito de fazer a sua exclusão do est

APA, Harvard, Vancouver, ISO, and other styles

8

Åkerström, Emelie. "Real-time Outlier Detection using Unbounded Data Streaming and Machine Learning." Thesis, Luleå tekniska universitet, Datavetenskap, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-80044.

Full text

Abstract:

Accelerated advancements in technology, the Internet of Things, and cloud computing have spurred an emergence of unstructured data that is contributing to rapid growth in data volumes. No human can manage to keep up with monitoring and analyzing these unbounded data streams and thus predictive and analytic tools are needed. By leveraging machine learning this data can be converted into insights which are enabling datadriven decisions that can drastically accelerate innovation, improve user experience, and drive operational efficiency. The purpose of this thesis is to design and implement a sys

APA, Harvard, Vancouver, ISO, and other styles

9

Dao, Quang Hoan <1992&gt. "Anomaly detection with time series forecasting." Master's Degree Thesis, Università Ca' Foscari Venezia, 2020. http://hdl.handle.net/10579/17320.

Full text

Abstract:

Anomaly detection time series is a very large and complex field. In recent years, several techniques based on data science were designed in order to improve the efficiency of methods developed for this purpose. In this paper, we introduce Recurrent Neural Networks (RNNs) with LSTM units, ARIMA and Facebook Prophet library for dectecting the anomalies with time series forcasting. Due to the challenges in obtaining labeled anomaly datasets, an unsupervised approach is employed. Unsupervised anomaly detection is the process of finding outlying records in a given dataset without prior need for tra

APA, Harvard, Vancouver, ISO, and other styles

10

Audibert, Julien. "Unsupervised anomaly detection in time-series." Electronic Thesis or Diss., Sorbonne université, 2021. http://www.theses.fr/2021SORUS358.

Full text

Abstract:

La détection d'anomalies dans les séries temporelles multivariées est un enjeu majeur dans de nombreux domaines. La complexité croissante des systèmes et l'explosion de la quantité de données ont rendu son automatisation indispensable. Cette thèse propose une méthode non supervisée de détection d'anomalies dans les séries temporelles multivariées appelée USAD. Cependant, les méthodes de réseaux de neurones profonds souffrent d'une limitation dans leur capacité à extraire des caractéristiques des données puisqu'elles ne s'appuient que sur des informations locales. Afin d'améliorer les performan

APA, Harvard, Vancouver, ISO, and other styles

11

Sperl, Ryan E. "Hierarchical Anomaly Detection for Time Series Data." Wright State University / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=wright1590709752916657.

Full text

APA, Harvard, Vancouver, ISO, and other styles

12

Sánchez, Enríquez Heider Ysaías. "Anomaly detection in streaming multivariate time series." Tesis, Universidad de Chile, 2017. http://repositorio.uchile.cl/handle/2250/149078.

Full text

Abstract:

Doctor en Ciencias, Mención Computación<br>Este trabajo de tesis presenta soluciones para al problema de detección de anomalı́as en flujo de datos multivariantes. Dado una subsequencia de serie temporal (una pequeña parte de la serie original) como entrada, uno quiere conocer si este corresponde a una observación normal o es una anomalı́a, con respecto a la información histórica. Pueden surgir dificultades debido principalmente a que los tipos de anomalı́a son desconocidos. Además, la detección se convierte en una tarea costosa debido a la gran cantidad de datos y a la existencia de vari

APA, Harvard, Vancouver, ISO, and other styles

13

Tinawi, Ihssan. "Machine learning for time series anomaly detection." Thesis, Massachusetts Institute of Technology, 2019. https://hdl.handle.net/1721.1/123129.

Full text

Abstract:

This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.<br>Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2019<br>Cataloged from student-submitted PDF version of thesis.<br>Includes bibliographical references (page 55).<br>In this thesis, I explored machine learning and other statistical techniques for anomaly detection on time series data obtained from Internet-of-Things sensors. The data, obtained from satellite telemetry signals, were

APA, Harvard, Vancouver, ISO, and other styles

14

Roth, Jennifer M. "A Time Series Approach to Removing Outlying Data Points from Bluetooth Vehicle Speed Data." University of Akron / OhioLINK, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=akron1289758088.

Full text

APA, Harvard, Vancouver, ISO, and other styles

15

Ji, Kang Hyeun. "Transient signal detection using GPS position time series." Thesis, Massachusetts Institute of Technology, 2011. http://hdl.handle.net/1721.1/69466.

Full text

Abstract:

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Earth, Atmospheric, and Planetary Sciences, 2011.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (p. 229-243).<br>Continuously operating Global Positioning System (GPS) networks record station position changes with millimeter-level accuracy and have revealed transient deformations on various spatial and temporal scales. However, the transient deformation may not be easily identified from the position time series because of low signal-to-noise ratios (SNR), correlated noise in space and time and la

APA, Harvard, Vancouver, ISO, and other styles

16

MACARO, CHRISTIAN. "Topics on unobserved component detection for time series." Doctoral thesis, Università degli Studi di Roma "Tor Vergata", 2008. http://hdl.handle.net/2108/691.

Full text

Abstract:

The Impact of Vintage on the Persistence of Gross Domestic Product Shocks. The first chapter of the thesis aims to demonstrate that the data revision process affects the persistence of gross domestic product shocks. The analysis is based on two alternative models, the Fractional Unit Root and the Linear Trend, and it benefits from new semiparametric procedures. The analysis of results seems to suggest that changes in the definition of the output significantly affects the performance of the models which are typically used to study the GDP series. - Seasonality in HighFrequency Data. T

APA, Harvard, Vancouver, ISO, and other styles

17

Lindroth, Henriksson Amelia. "Unsupervised Anomaly Detection on Time Series Data: An Implementation on Electricity Consumption Series." Thesis, KTH, Matematisk statistik, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-301731.

Full text

Abstract:

Digitization of the energy industry, introduction of smart grids and increasing regulation of electricity consumption metering have resulted in vast amounts of electricity data. This data presents a unique opportunity to understand the electricity usage and to make it more efficient, reducing electricity consumption and carbon emissions. An important initial step in analyzing the data is to identify anomalies. In this thesis the problem of anomaly detection in electricity consumption series is addressed using four machine learning methods: density based spatial clustering for applications with

APA, Harvard, Vancouver, ISO, and other styles

18

Yacob, Andreas, and Olof Nilsson. "Non-parametric anomaly detection in sentiment time series data." Thesis, Uppsala universitet, Institutionen för teknikvetenskaper, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-251645.

Full text

Abstract:

The importance of finding extreme events or unexpected patterns has increased over the last two decades, mainly due rapid advancements in technology. These events or patterns are referred to as anomalies. This thesis focuses on detecting anomalies in form of sudden peaks occurring in time series generated from online text analysis in Gavagai’s live environment. To our knowledge there exist a limited number of sequential peak detection models applicable in this domain. We introduce a novel technique using the Local Outlier Factor model as well as a model built on simple linear regression with a

APA, Harvard, Vancouver, ISO, and other styles

19

Barham, S. Y. "Time series analysis in the detection of breast cancer." Thesis, Bucks New University, 1987. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.384665.

Full text

APA, Harvard, Vancouver, ISO, and other styles

20

Vendramin, Nicoló. "Unsupervised Anomaly Detection on Multi-Process Event Time Series." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-254885.

Full text

Abstract:

Establishing whether the observed data are anomalous or not is an important task that has been widely investigated in literature, and it becomes an even more complex problem if combined with high dimensional representations and multiple sources independently generating the patterns to be analyzed. The work presented in this master thesis employs a data-driven pipeline for the definition of a recurrent auto-encoder architecture to analyze, in an unsupervised fashion, high-dimensional event time-series generated by multiple and variable processes interacting with a system. Facing the above menti

APA, Harvard, Vancouver, ISO, and other styles

21

Granlund, Oskar. "Unsupervised anomaly detection on log-based time series data." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-265534.

Full text

Abstract:

Due to a constant increase in the number of connected devices and there is an increased demand for confidentiality, availability, and integrity on applications. This thesis was focused on unsupervised anomaly detection in data centers. It evaluates how suitable open source state-of-the-art solutions are at finding abnormal trends and patterns in log-based data streams. The methods used in this work are Principal component analysis (PCA), LogCluster, and Hierarchical temporal memory (HTM). They were evaluated using F-score on a real data set from an Apache access log. The data set was carefully

APA, Harvard, Vancouver, ISO, and other styles

22

Jacob, Vincent. "High-Dimensional Time Series Anomaly Detection over Heterogeneous Domains." Electronic Thesis or Diss., Institut polytechnique de Paris, 2024. http://www.theses.fr/2024IPPAX068.

Full text

Abstract:

L'adoption généralisée des services numériques, ainsi que l'échelle et la complexité de leur fonctionnement, ont rendu les incidents dans les opérations informatiques de plus en plus probables, diversifiés et impactants pour les entreprises de logiciels, créant ainsi le besoin de solutions automatisées pour les prévenir. Pour répondre à ce besoin, cette thèse se concentre sur le problème de la détection d'anomalies dans les séries temporelles de grande dimension, dans le cadre du domaine émergent de l'"Intelligence Artificielle pour les Opérations Informatiques" (AIOps).Cette thèse propose tou

APA, Harvard, Vancouver, ISO, and other styles

23

Kong, Lanfang. "Explainable algorithms for anomaly detection and time series forecasting." Electronic Thesis or Diss., Institut polytechnique de Paris, 2024. http://www.theses.fr/2024IPPAT039.

Full text

Abstract:

L'intelligence artificielle a montré des performances dominantes dans le domaine de l'exploration de données, avec des applications dans divers domaines, y compris des domaines critiques tels que la médecine, la finance, la justice, etc. En conséquence, l'explicabilité des modèles de boîte noire devient de plus en plus exigeante. Nous nous concentrons sur deux applications spécifiques : la détection d'anomalies et la prévision de séries chronologiques, et présentons XTREK et ADAPATCH pour chaque tâche, respectivement. XTREK est une approche non supervisée basée sur un arbre pour la détection d

APA, Harvard, Vancouver, ISO, and other styles

24

Du, Yang. "Comparison of change-point detection algorithms for vector time series." Thesis, Linköpings universitet, Statistik, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-59925.

Full text

Abstract:

Change-point detection aims to reveal sudden changes in sequences of data. Special attention has been paid to the detection of abrupt level shifts, and applications of such techniques can be found in a great variety of fields, such as monitoring of climate change, examination of gene expressions and quality control in the manufacturing industry. In this work, we compared the performance of two methods representing frequentist and Bayesian approaches, respectively. The frequentist approach involved a preliminary search for level shifts using a tree algorithm followed by a dynamic programming al

APA, Harvard, Vancouver, ISO, and other styles

25

Santos, Rui Pedro Silvestre dos. "Time series morphological analysis applied to biomedical signals events detection." Master's thesis, Faculdade de Ciências e Tecnologia, 2011. http://hdl.handle.net/10362/10227.

Full text

Abstract:

Dissertation submitted in the fufillment of the requirements for the Degree of Master in Biomedical Engineering<br>Automated techniques for biosignal data acquisition and analysis have become increasingly powerful, particularly at the Biomedical Engineering research field. Nevertheless, it is verified the need to improve tools for signal pattern recognition and classification systems, in which the detection of specific events and the automatic signal segmentation are preliminary processing steps. The present dissertation introduces a signal-independent algorithm, which detects significant ev

APA, Harvard, Vancouver, ISO, and other styles

26

Wolpher, Maxim. "Anomaly Detection in Unstructured Time Series Datausing an LSTM Autoencoder." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-231368.

Full text

Abstract:

An exploration of anomaly detection. Much work has been done on the topic of anomalyd etection, but what seems to be lacking is a dive into anomaly detection of unstructuredand unlabeled data. This thesis aims to determine the efctiveness of combining recurrentneural networks with autoencoder structures for sequential anomaly detection. The use of an LSTM autoencoder will be detailed, but along the way there will also be backgroundon time-independent anomaly detection using Isolation Forests and Replicator Neural Networks on the benchmark DARPA dataset. The empirical results in this thesis sho

APA, Harvard, Vancouver, ISO, and other styles

27

Berenji, Ardestani Sarah. "Time Series Anomaly Detection and Uncertainty Estimation using LSTM Autoencoders." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-281354.

Full text

Abstract:

The goal of this thesis is to implement an anomaly detection tool using LSTM autoencoder and apply a novel method for uncertainty estimation using Bayesian NeuralNetworks (BNNs) based on a paper from Uber research group [1]. Having a reliable anomaly detection tool and accurate uncertainty estimation is critical in many fields. At Telia, such a tool can be used in many different data domains like device logs to detect abnormal behaviours. Our method uses an autoencoder to extract important features and learn the encoded representation of the time series. This approach helps to capture testing

APA, Harvard, Vancouver, ISO, and other styles

28

Wasnik, Sachinkumar. "Fatigue Detection in EEG Time Series Data Using Deep Learning." Thesis, The University of Sydney, 2021. https://hdl.handle.net/2123/24917.

Full text

Abstract:

Fatigue has widespread effects on the brain’s executive function, reaction time and information processing, causing loss of alertness, that affect safety, and productivity. There are various subjective and behavioural methods to measure fatigue. However, none of them is precise. The work in this thesis employs physiological measures such as heart rate, blood pressure, and breathing that are objective and quantitative indicators. These are thought to provide reliable measures of fatigue and may be easier to deploy in real world scenarios, compared to the subjective or behavioural methods. In p

APA, Harvard, Vancouver, ISO, and other styles

29

Thorén, Sofia, and Richard Sörberg. "Anomaly Detection in Signaling Data Streams : A Time-Series Approach." Thesis, Umeå universitet, Institutionen för matematik och matematisk statistik, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-139773.

Full text

Abstract:

This work has aimed to develop a method which can be used in order to detect anomalies in signaling data streams at a telecommunication company. It has been done by modeling and evaluating three prediction models and two detection methods. The prediction models which have been implemented are Autoregressive Integrated Moving Average (ARIMA), Holt-Winters and a Benchmark model, furthermore have two detection methods been tested; Method 1 (M1), which is based on a robust evaluation of previous prediction errors and Method 2 (M2), which is based on the standard deviation in previous data. From th

APA, Harvard, Vancouver, ISO, and other styles

30

Haddad, Josef, and Carl Piehl. "Unsupervised anomaly detection in time series with recurrent neural networks." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-259655.

Full text

Abstract:

Artificial neural networks (ANN) have been successfully applied to a wide range of problems. However, most of the ANN-based models do not attempt to model the brain in detail, but there are still some models that do. An example of a biologically constrained ANN is Hierarchical Temporal Memory (HTM). This study applies HTM and Long Short-Term Memory (LSTM) to anomaly detection problems in time series in order to compare their performance for this task. The shape of the anomalies are restricted to point anomalies and the time series are univariate. Pre-existing implementations that utilise these

APA, Harvard, Vancouver, ISO, and other styles

31

Mian, Ammar. "Contributions to SAR Image Time Series Analysis." Thesis, Université Paris-Saclay (ComUE), 2019. http://www.theses.fr/2019SACLC074/document.

Full text

Abstract:

La télédétection par Radar à Synthèse d’Ouverture (RSO) offre une opportunité unique d’enregistrer, d’analyser et de prédire l’évolution de la surface de la Terre. La dernière décennie a permis l’avènement de nombreuses missions spatiales équipées de capteurs RSO (Sentinel-1, UAVSAR, TerraSAR X, etc.), ce qui a engendré une rapide amélioration des capacités d’acquisition d’images de la surface de la Terre. Le nombre croissant d’observations permet maintenant de construire des bases de données caractérisant l’évolution temporelle d’images, augmentant considérablement l’intérêt de l’analyse de s

APA, Harvard, Vancouver, ISO, and other styles

32

Taillade, Thibault. "A new strategy for change detection in SAR time-series : application to target detection." Thesis, université Paris-Saclay, 2020. http://www.theses.fr/2020UPAST050.

Full text

Abstract:

La détection de cibles telles que des navires ou des véhicules dans les images SAR (Synthetic Aperture radar) est un défi important pour la surveillance et la sécurité. Dans certains environnements tels que les zones urbaines, portuaires ou les forêts observées à basses fréquences radar, la détection de ces objets devient difficile en raison des propriétés de rétrodiffusion élevées de l'environnement. Pour résoudre ce problème, la détection de changement (CD) entre différentes images SAR permet de supprimer l'effet de l'environnement et ainsi une meilleur détection des cibles. Cependant, dans

APA, Harvard, Vancouver, ISO, and other styles

33

Ferreira, Leonardo Nascimento. "Time series data mining using complex networks." Universidade de São Paulo, 2017. http://www.teses.usp.br/teses/disponiveis/55/55134/tde-01022018-144118/.

Full text

Abstract:

A time series is a time-ordered dataset. Due to its ubiquity, time series analysis is interesting for many scientific fields. Time series data mining is a research area that is intended to extract information from these time-related data. To achieve it, different models are used to describe series and search for patterns. One approach for modeling temporal data is by using complex networks. In this case, temporal data are mapped to a topological space that allows data exploration using network techniques. In this thesis, we present solutions for time series data mining tasks using complex netw

APA, Harvard, Vancouver, ISO, and other styles

34

Aboode, Adam. "Anomaly Detection in Time Series Data Based on Holt-Winters Method." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-226344.

Full text

Abstract:

In today's world the amount of collected data increases every day, this is a trend which is likely to continue. At the same time the potential value of the data does also increase due to the constant development and improvement of hardware and software. However, in order to gain insights, make decisions or train accurate machine learning models we want to ensure that the data we collect is of good quality. There are many definitions of data quality, in this thesis we focus on the accuracy aspect. One method which can be used to ensure accurate data is to monitor for and alert on anomalies. In

APA, Harvard, Vancouver, ISO, and other styles

35

Liu, R. Q., and Ch Jacobi. "Piecewise linear trend detection in mesosphere/lower thermosphere wind time series." Universität Leipzig, 2010. https://ul.qucosa.de/id/qucosa%3A16361.

Full text

Abstract:

A piecewise linear model is developed to detect climatic trends and possible structural changes in time series with a priori unknown number and positions of breakpoints. The initial noise is allowed to be interpreted by the first- and second-order autoregressive models. The goodness of fit of candidate models, if the residuals are accepted as normally distributed white noise, is evaluated using the Schwarz Bayesian Information Criterion. The uncertainties of all modeled trend parameters are estimated using the Monte-Carlo method. The model is applied to the mesosphere/lower thermosphere winds

APA, Harvard, Vancouver, ISO, and other styles

36

Кіріченко, Л. О., В. Г. Кобзєв, and Є. Д. Федоренко. "Data Mining methods for detection of collective anomalies in time series." Thesis, Національна академія Національної гвардії України, 2021. https://openarchive.nure.ua/handle/document/16449.

Full text

Abstract:

The paper considers the approach to the detection of collective anomalies in time series, based on the use of clustering methods, in particular the method of k-means, as well as the effectiveness of their application.

APA, Harvard, Vancouver, ISO, and other styles

37

Novacic, Jelena, and Kablai Tokhi. "Implementation of Anomaly Detection on a Time-series Temperature Data set." Thesis, Malmö universitet, Fakulteten för teknik och samhälle (TS), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:mau:diva-20375.

Full text

Abstract:

Aldrig har det varit lika aktuellt med hållbar teknologi som idag. Behovet av bättre miljöpåverkan inom alla områden har snabbt ökat och energikonsumtionen är ett av dem. En enkel lösning för automatisk kontroll av energikonsumtionen i smarta hem är genom mjukvara. Med dagens IoT teknologi och maskinlärningsmodeller utvecklas den mjukvarubaserade hållbara livsstilen allt mer. För att kontrollera ett hushålls energikonsumption måste plötsligt avvikande beteenden detekteras och regleras för att undvika onödig konsumption. Detta examensarbete använder en tidsserie av temperaturdata för att implem

APA, Harvard, Vancouver, ISO, and other styles

38

Stafford, William B. "Sequential pattern detection and time series models for predicting IED attacks." Thesis, Monterey, Calif. : Naval Postgraduate School, 2009. http://edocs.nps.edu/npspubs/scholarly/theses/2009/Mar/09Mar%5FStafford.pdf.

Full text

Abstract:

Thesis (M.S. in Information Technology Management)--Naval Postgraduate School, March 2009.<br>Thesis Advisor(s): Kamel, Magdi. "March 2009." Description based on title screen as viewed on April 24, 2009. Author(s) subject terms: Sequential Pattern Detection, Time Series, Predicting IED Attacks, Data Mining. Includes bibliographical references (p. 77). Also available in print.

APA, Harvard, Vancouver, ISO, and other styles

39

Combettes, Sylvain. "Symbolic representations of time series." Electronic Thesis or Diss., université Paris-Saclay, 2024. http://www.theses.fr/2024UPASM002.

Full text

Abstract:

Les objectifs de cette thèse sont de définir de nouvelles représentations symboliques et des mesures de distance adaptées aux séries temporelles pouvant être multivariées et non-stationnaires. De plus, elles doivent préserver l'information temporelle, être interprétables et rapides à calculer. Nous passons en revue les représentations symboliques de séries temporelles, ainsi que les mesures de distance sur séries temporelles, chaînes de caractères et séquences symboliques (qui résultent d'un processus de symbolisation).Nous proposons deux contributions: ASTRIDE pour un ensemble de séries tempo

APA, Harvard, Vancouver, ISO, and other styles

40

Jorge, Ana Maria Nabais. "Sobre a Definição de Outlier no Domínio Específico dos Modelos Lineares e Séries Temporais." Master's thesis, Instituto Superior de Economia e Gestão, 1999. http://hdl.handle.net/10400.5/4017.

Full text

Abstract:

Mestrado em Matemática Aplicada à Economia e Gestão<br>0 que são outliers e o que é o problema outlier? O principal objectivo desta dissertação é fazer o ponto da situação sobre o conceito outlier e como este é tratado no domínio específico dos modelos lineares e das séries temporais, para além de tentar saber como é que os mais modernos pacotes estatísticos tratam o tema. Assim, o nosso trabalho encontra-se dividido em seis capítulos. No primeiro capítulo, são enunciados os objectivos da presente dissertação e as suas motivações. No segundo capítulo, faz-se um apanhado de como o conceito outl

APA, Harvard, Vancouver, ISO, and other styles

41

Chen, Tiankai M. Eng Massachusetts Institute of Technology. "Anomaly detection in semiconductor manufacturing through time series forecasting using neural networks." Thesis, Massachusetts Institute of Technology, 2018. http://hdl.handle.net/1721.1/120245.

Full text

Abstract:

Thesis: M. Eng. in Advanced Manufacturing and Design, Massachusetts Institute of Technology, Department of Mechanical Engineering, 2018.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (pages 92-94).<br>Semiconductor manufacturing provides unique challenges to the anomaly detection problem. With multiple recipes and multivariate data, it is difficult for engineers to reliably detect anomalies in the manufacturing process. An experimental study into anomaly detection through time series forecasting is carried out with application to a plasma etch case study. The

APA, Harvard, Vancouver, ISO, and other styles

42

Farahani, Marzieh. "Anomaly Detection on Gas Turbine Time-series’ Data Using Deep LSTM-Autoencoder." Thesis, Umeå universitet, Institutionen för datavetenskap, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-179863.

Full text

Abstract:

Anomaly detection with the aim of identifying outliers plays a very important role in various applications (e.g., online spam, manufacturing, finance etc.). An automatic and reliable anomaly detection tool with accurate prediction is essential in many domains. This thesis proposes an anomaly detection method by applying deep LSTM (long short-term memory) especially on time-series data. By validating on real-worlddata at Siemens Industrial Turbomachinery (SIT), the proposed methods hows promising performance, and can be employed in different data domains like device logs of turbine machines to

APA, Harvard, Vancouver, ISO, and other styles

43

Piyadi, Gamage Ramadha D. "Empirical Likelihood For Change Point Detection And Estimation In Time Series Models." Bowling Green State University / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=bgsu1495457528719879.

Full text

APA, Harvard, Vancouver, ISO, and other styles

44

Chambon, Stanislas. "Learning from electrophysiology time series during sleep : from scoring to event detection." Thesis, Université Paris-Saclay (ComUE), 2018. http://www.theses.fr/2018SACLT014.

Full text

Abstract:

Le sommeil est un phénomène biologique universel complexe et encore peu compris. La méthode de référence actuelle pour caractériser les états de vigilance au cours du sommeil est la polysomnographie (PSG) qui enregistre de manière non invasive à la surface de la peau, les modifications électrophysiologiques de l’activité cérébrale (électroencéphalographie, EEG), oculaire (électro-oculographie, EOG) et musculaire (électromyographie, EMG). Traditionnellement, les signaux électrophysiologiques sont ensuite analysés par un expert du sommeil qui annote manuellement les évènements d’intérêt comme le

APA, Harvard, Vancouver, ISO, and other styles

45

Chambon, Stanislas. "Learning from electrophysiology time series during sleep : from scoring to event detection." Electronic Thesis or Diss., Université Paris-Saclay (ComUE), 2018. http://www.theses.fr/2018SACLT014.

Full text

Abstract:

Le sommeil est un phénomène biologique universel complexe et encore peu compris. La méthode de référence actuelle pour caractériser les états de vigilance au cours du sommeil est la polysomnographie (PSG) qui enregistre de manière non invasive à la surface de la peau, les modifications électrophysiologiques de l’activité cérébrale (électroencéphalographie, EEG), oculaire (électro-oculographie, EOG) et musculaire (électromyographie, EMG). Traditionnellement, les signaux électrophysiologiques sont ensuite analysés par un expert du sommeil qui annote manuellement les évènements d’intérêt comme le

APA, Harvard, Vancouver, ISO, and other styles

46

Ravirala, Narayana. "Device signal detection methods and time frequency analysis." Diss., Rolla, Mo. : University of Missouri-Rolla, 2007. http://scholarsmine.umr.edu/thesis/pdf/Ravirala_09007dcc803fea67.pdf.

Full text

Abstract:

Thesis (M.S.)--University of Missouri--Rolla, 2007.<br>Vita. The entire thesis text is included in file. Title from title screen of thesis/dissertation PDF file (viewed March 18, 2008) Includes bibliographical references (p. 89-90).

APA, Harvard, Vancouver, ISO, and other styles

47

Alklid, Jonathan. "Time to Strike: Intelligent Detection of Receptive Clients : Predicting a Contractual Expiration using Time Series Forecasting." Thesis, Linnéuniversitetet, Institutionen för datavetenskap och medieteknik (DM), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-106217.

Full text

Abstract:

In recent years with the advances in Machine Learning and Artificial Intelligence, the demand for ever smarter automation solutions could seem insatiable. One such demand was identified by Fortnox AB, but undoubtedly shared by many other industries dealing with contractual services, who were looking for an intelligent solution capable of predicting the expiration date of a contractual period. As there was no clear evidence suggesting that Machine Learning models were capable of learning the patterns necessary to predict a contract's expiration, it was deemed desirable to determine subject feas

APA, Harvard, Vancouver, ISO, and other styles

48

Theissler, Andreas. "Detecting anomalies in multivariate time series from automotive systems." Thesis, Brunel University, 2013. http://bura.brunel.ac.uk/handle/2438/7902.

Full text

Abstract:

In the automotive industry test drives are conducted during the development of new vehicle models or as a part of quality assurance for series vehicles. During the test drives, data is recorded for the use of fault analysis resulting in millions of data points. Since multiple vehicles are tested in parallel, the amount of data that is to be analysed is tremendous. Hence, manually analysing each recording is not feasible. Furthermore the complexity of vehicles is ever-increasing leading to an increase of the data volume and complexity of the recordings. Only by effective means of analysing the

APA, Harvard, Vancouver, ISO, and other styles

49

Kwong, Siu-shing. "Detection of determinism of nonlinear time series with application to epileptic electroencephalogram analysis." View the Table of Contents & Abstract, 2005. http://sunzi.lib.hku.hk/hkuto/record/B35512222.

Full text

APA, Harvard, Vancouver, ISO, and other styles

50

Eriksson, Tilda. "Change Detection in Telecommunication Data using Time Series Analysis and Statistical Hypothesis Testing." Thesis, Linköpings universitet, Matematiska institutionen, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-94530.

Full text

Abstract:

In the base station system of the GSM mobile network there are a large number of counters tracking the behaviour of the system. When the software of the system is updated, we wish to find out which of the counters that have changed their behaviour. This thesis work has shown that the counter data can be modelled as a stochastic time series with a daily profile and a noise term. The change detection can be done by estimating the daily profile and the variance of the noise term and perform statistical hypothesis tests of whether the mean value and/or the daily profile of the counter data before

APA, Harvard, Vancouver, ISO, and other styles

We offer discounts on all premium plans for authors whose works are included in thematic literature selections. Contact us to get a unique promo code!