Two-dimensional trend analysis of time series of complex technical objects diagnostic parameters

2019 ◽  
Author(s):  
V. Myrhorod ◽  
I. Hvozdeva ◽  
Y. Derenh
Keyword(s):  
Time Series ◽  
Trend Analysis ◽  
Two Dimensional ◽  
Diagnostic Parameters ◽  
Analysis Of Time Series

Trend analysis of time-series data: A novel method for untargeted metabolite discovery

2010 ◽  
Vol 663 (1) ◽  
pp. 98-104 ◽  
Author(s):  
Sonja Peters ◽  
Hans-Gerd Janssen ◽  
Gabriel Vivó-Truyols
Keyword(s):  
Time Series ◽  
Trend Analysis ◽  
Time Series Data ◽  
Series Data ◽  
Novel Method ◽  
Analysis Of Time Series

scholarly journals Mapping Mountain Pine Beetle Mortality through Growth Trend Analysis of Time-Series Landsat Data

2014 ◽  
Vol 6 (6) ◽  
pp. 5696-5716 ◽  
Author(s):  
Lu Liang ◽  
Yanlei Chen ◽  
Todd Hawbaker ◽  
Zhiliang Zhu ◽  
Peng Gong
Keyword(s):  
Time Series ◽  
Trend Analysis ◽  
Mountain Pine Beetle ◽  
Landsat Data ◽  
Growth Trend ◽  
Mountain Pine ◽  
Pine Beetle ◽  
Analysis Of Time Series

scholarly journals Changes of characteristics of daily precipitation and runoff in the High Tatra Mountains, Slovakia over the last fifty years

2013 ◽  
Vol 43 (2) ◽  
pp. 157-177 ◽  
Author(s):  
Svetlana Bičárová ◽  
Ladislav Holko
Keyword(s):  
Time Series ◽  
Trend Analysis ◽  
Daily Precipitation ◽  
Flow Characteristics ◽  
Data Series ◽  
Precipitation Data ◽  
Tatra Mountains ◽  
Maximum Flows ◽  
High Tatra Mountains ◽  
Analysis Of Time Series

Abstract The article presents the results of the analysis of time series of daily precipitation and runoff at selected places in the highest part of the Western Carpathians. It was focused on both wet and dry periods in precipitation and runoff data series. The precipitation data were analysed for a period 1961-2010. They revealed a significant increase of the number of days with daily precipitation 40-60 mm. Trend analysis for 67 analysed flow characteristics did not show statistically significant changes over the studied period. The focus was given particularly to the characteristics of the maximum and minimum flows, i.e. 3- and 7- day minimum flows, 1-, 3- and 7-day maximum flows. We found an increase of flows classified as small floods in two of three mountain catchments in the study area in the last decade (2001-2010). It may be linked to the above increased number of days with daily precipitation reaching 40-60 mm.

Correlation in the heart rate data

1998 ◽  
Vol 2 ◽  
pp. 141-148
Author(s):  
J. Ulbikas ◽  
A. Čenys ◽  
D. Žemaitytė ◽  
G. Varoneckas
Keyword(s):  
Nonlinear Dynamics ◽  
Experimental Data ◽  
Heart Rate ◽  
Time Series ◽  
Cardiovascular Function ◽  
Statistical Properties ◽  
Rate Data ◽  
Heart Rate Data ◽  
Dynamical Nature ◽  
Analysis Of Time Series

Variety of methods of nonlinear dynamics have been used for possibility of an analysis of time series in experimental physiology. Dynamical nature of experimental data was checked using specific methods. Statistical properties of the heart rate have been investigated. Correlation between of cardiovascular function and statistical properties of both, heart rate and stroke volume, have been analyzed. Possibility to use a data from correlations in heart rate for monitoring of cardiovascular function was discussed.

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