scholarly journals Dynamic Correlation Analysis Method of Air Pollutants in Spatio-Temporal Analysis

2020 ◽  
Vol 17 (1) ◽  
pp. 360 ◽  
Author(s):  
Yu-ting Bai ◽  
Xue-bo Jin ◽  
Xiao-yi Wang ◽  
Xiao-kai Wang ◽  
Ji-ping Xu
Keyword(s):  
Correlation Analysis ◽  
Temporal Analysis ◽  
Pollution Source ◽  
Analysis Method ◽  
Dynamic Features ◽  
Dynamic Correlation ◽  
Critical Issues ◽  
Correlation Analysis Method ◽  
Spatio Temporal ◽  
Grey Relational

Pollutant analysis and pollution source tracing are critical issues in air quality management, in which correlation analysis is important for pollutant relation modeling. A dynamic correlation analysis method was proposed to meet the real-time requirement in atmospheric management. Firstly, the spatio-temporal analysis framework was designed, in which the process of data monitoring, correlation calculation, and result presentation were defined. Secondly, the core correlation calculation method was improved with an adaptive data truncation and grey relational analysis. Thirdly, based on the general framework and correlation calculation, the whole algorithm was proposed for various analysis tasks in time and space, providing the data basis for ranking and decision on pollutant effects. Finally, experiments were conducted with the practical data monitored in an industrial park of Hebei Province, China. The different pollutants in multiple monitoring stations were analyzed crosswise. The dynamic features of the results were obtained to present the variational correlation degrees from the proposed and contrast methods. The results proved that the proposed dynamic correlation analysis could quickly acquire atmospheric pollution information. Moreover, it can help to deduce the influence relation of pollutants in multiple locations.

Application of Cross-correlation Analysis Method for Measurement of the Fluid Flow Rate Based on X-ray Radiation

2019 ◽  
Vol 11 (1) ◽  
pp. 01025-1-01025-5 ◽  
Author(s):  
N. A. Borodulya ◽  
◽  
R. O. Rezaev ◽  
S. G. Chistyakov ◽  
E. I. Smirnova ◽  
...  
Keyword(s):  
Fluid Flow ◽  
Correlation Analysis ◽  
Flow Rate ◽  
Cross Correlation ◽  
Fluid Flow Rate ◽  
Analysis Method ◽  
X Ray ◽  
Cross Correlation Analysis ◽  
Correlation Analysis Method

scholarly journals MULTI-DIMENSIONAL ERROR ANALYSIS OF NEARSHORE WAVE MODELING TOOLS, WITH APPLICATION TOWARD DATA-DRIVEN BOUNDARY CORRECTION

2011 ◽  
Vol 1 (32) ◽  
pp. 67
Author(s):  
Boyang Jiang ◽  
James Kaihatu
Keyword(s):  
Boundary Conditions ◽  
Initial Boundary ◽  
Temporal Analysis ◽  
Analysis Method ◽  
Modeling Tools ◽  
Dimensional Error ◽  
Lateral Boundary Conditions ◽  
Boundary Information ◽  
The Subject ◽  
Spatio Temporal

As the forecasting models become more sophisticated in their physics and possible depictions of the nearshore hydrodynamics, they also become increasingly sensitive to errors in the inputs, such as errors in the specification of boundary information (lateral boundary conditions, initial boundary conditions, etc). Evaluation of the errors on the boundary is less straightforward, and is the subject of this study. The model under investigation herein is the Delft3D modeling suite, developed at Deltares (formerly Delft Hydraulics) in Delft, the Netherlands. Coupling of the wave (SWAN) and hydrodynamic (FLOW) model requires care at the lateral boundaries in order to balance run time and error growth. To this extent, we will use perturbation method and spatio-temporal analysis method such as Empirical Orthogonal Function (EOF) analysis to determine the various scales of motion in the flow field and the extent of their response to imposed boundary errors.

scholarly journals Correlation analysis between multifractal characteristics of regional geomorphology and development of geological disasters

2021 ◽  
Vol 25 (1) ◽  
pp. 49-55
Author(s):  
Yiying Xiong
Keyword(s):  
Correlation Analysis ◽  
Spatial Relationship ◽  
Analysis Method ◽  
Self Similarity ◽  
Geological Disasters ◽  
Geological Disaster ◽  
Correlation Analysis Method ◽  
Fractal Spectrum ◽  
Fractal Characteristics ◽  
Relationship Of

In view of the inaccuracy of the traditional correlation analysis method, this paper proposes a correlation analysis method between the multifractal characteristics of regional landforms and the development of geological disasters. Firstly, the multifractal characteristics of regional landforms are described by using the basic fractal characteristics of self-similarity or scale invariance. Then the corresponding relation table is established according to the width of the fractal spectrum and the number of landslides and hidden dangers, and the spatial relationship of geological disaster development is analyzed. Combined with the above-mentioned spatial relationship of geological disaster development and the multifractal characteristic data of regional landforms, the correlation coefficient between the two is calculated to complete the correlation analysis between the multifractal characteristics of regional geomorphology and the development of geological disasters. The experimental results show that compared with the traditional correlation analysis method, the correlation analysis results of the multifractal characteristics of regional geomorphology and the development of geological disasters are more accurate.

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