Results 51 to 60 of about 1,148,061 (201)
Application of Change-Point Detection to a Structural Component of Water Quality Variables
, 2011 In this study, methodologies were developed in statistical time series models, such as multivariate state-space models, to be applied to water quality variables in a river basin.
Gonçalves, A. Manuela +7 more
core +1 more source
Safety, 2020 Trends and underlying patterns should be identified in the timely distribution of road traffic offenses to increase traffic safety. In this study, a time series analysis was used to study the incidence rate of road traffic violations on Iranian rural ...
Milad Delavary +2 more
doaj +1 more source
Entropy, 2021 We consider a retrospective change-point detection problem for multidimensional time series of arbitrary nature (in particular, panel data). Change-points are the moments at which the changes in generating mechanism occur.
Alexandra Piryatinska, Boris Darkhovsky
doaj +1 more source
Application and Optimization of Algorithms for Pressure Wave Evaluation Based on Measurement Data
Applied Sciences, 2022 Leakages can occur in a district heating network, resulting in high economical damage. The propagating pressure wave resulting from large, spontaneous leakages reaches sensors at different locations in the network. This leads to pressure drops registered
Kai Vahldiek +3 more
doaj +1 more source
Model-Free Change Point Detection for Mixing Processes
IEEE Open Journal of Control SystemsThis paper considers the change point detection problem under dependent samples. In particular, we provide performance guarantees for the MMD-CUSUM test under exponentially $\alpha$, $\beta$, and fast $\phi$-mixing processes, which significantly expands ...
Hao Chen +3 more
doaj +1 more source
Differentially Private Change-Point Detection
CoRR, 2018 The change-point detection problem seeks to identify distributional changes at an unknown change-point k* in a stream of data. This problem appears in many important practical settings involving personal data, including biosurveillance, fault detection, finance, signal detection, and security systems.
Rachel Cummings +4 more
openaire +3 more sources
ruptures: change point detection in Python
CoRR, 2018 ruptures is a Python library for offline change point detection. This package provides methods for the analysis and segmentation of non-stationary signals. Implemented algorithms include exact and approximate detection for various parametric and non-parametric models.
Charles Truong +2 more
openaire +2 more sources
An Evaluation of Change Point Detection Algorithms
CoRR, 2020 For code and data, see https://github.com/alan-turing-institute/TCPDBench ; Changelog in ...
Gerrit J. J. van den Burg +1 more
openaire +2 more sources
Change-point detection in a sequence of bags-of-data [PDF]
2016 IEEE 32nd International Conference on Data Engineering (ICDE), 2015 In this paper, the limitation that is prominent in most existing works of change-point detection methods is addressed by proposing a nonparametric, computationally efficient method. The limitation is that most works assume that each data point observed at each time step is a single multi-dimensional vector. However, there are many situations where this
Kensuke Koshijima +2 more
openaire +1 more source
Change point detection in risk adjusted control charts
, 2011 Precise identification of the time when a change in a clinical process has occurred enables experts to identify a potential special cause more effectively. In this article, we develop change point estimation methods for a clinical dichotomous process in
Kerrie Mengersen +5 more
core +1 more source