A novel displacement prediction method using gated recurrent unit model with time series analysis in the Erdaohe landslide

2020 ◽  
Vol 105 (1) ◽  
pp. 783-813 ◽  
Author(s):  
Yong-gang Zhang ◽  
Jun Tang ◽  
Zheng-ying He ◽  
Junkun Tan ◽  
Chao Li
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Prediction Method ◽  
Displacement Prediction ◽  
Series Analysis ◽  
Unit Model ◽  
Gated Recurrent Unit

Prediction of Mine Gas Emission Based on Time Series Analysis

2012 ◽  
Vol 616-618 ◽  
pp. 450-454 ◽  
Author(s):  
Hai Dong Meng ◽  
Dong Yuan Zang ◽  
Yu Chen Song
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Prediction Method ◽  
Ar Model ◽  
Prediction Methods ◽  
Gas Emission ◽  
Gas Concentration ◽  
Series Analysis ◽  
Mine Gas

Because the variation of mine gas concentration is influenced by various factors, so it’s impossible for traditional prediction methods of mine gas emission to include all the factors. To solve the problem, the paper proposed a prediction method of mine gas emission based on AR model of time series analysis. The experiment results indicated that the method can predict mine gas emission accurately.

scholarly journals Nonlinear time series analysis of the fluctuations of the geomagnetic horizontal field

2002 ◽  
Vol 20 (2) ◽  
pp. 175-183 ◽  
Author(s):  
B. George ◽  
G. Renuka ◽  
K. Satheesh Kumar ◽  
C. P. Anil Kumar ◽  
C. Venugopal
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Correlation Dimension ◽  
Prediction Method ◽  
Nonlinear Time Series ◽  
Nonlinear Time Series Analysis ◽  
Suitable Model ◽  
Nonlinear Prediction ◽  
Series Analysis ◽  
Hourly Data

Abstract. A detailed nonlinear time series analysis of the hourly data of the geomagnetic horizontal intensity H measured at Kodaikanal (10.2° N; 77.5° E; mag: dip 3.5° N) has been carried out to investigate the dynamical behaviour of the fluctuations of H. The recurrence plots, spatiotemporal entropy and the result of the surrogate data test show the deterministic nature of the fluctuations, rejecting the hypothesis that H belong to the family of linear stochastic signals. The low dimensional character of the dynamics is evident from the estimated value of the correlation dimension and the fraction of false neighbours calculated for various embedding dimensions. The exponential decay of the power spectrum and the positive Lyapunov exponent indicate chaotic behaviour of the underlying dynamics of H. This is also supported by the results of the comparison of the chaotic characteristics of the time series of H with the pseudo-chaotic characteristics of coloured noise time series. We have also shown that the error involved in the short-term prediction of successive values of H, using a simple but robust, zero-order nonlinear prediction method, increases exponentially. It has also been suggested that there exists the possibility of characterizing the geomagnetic fluctuations in terms of the invariants in chaos theory, such as Lyapunov exponents and correlation dimension. The results of the analysis could also have implications in the development of a suitable model for the daily fluctuations of geomagnetic horizontal intensity.Key words. Geomagnetism and paleomagnetism (time variations, diurnal to secular) – History of geophysics (solar-planetary relationships) Magnetospheric physics (storms and substorms)

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