The application of fractal geometry analysis to groundwater exploration

Author(s):  
S Kusumayudha
2016 ◽  
Vol 17 (6) ◽  
pp. 1661-1673 ◽  
Author(s):  
A. R. Jameson ◽  
M. L. Larsen ◽  
A. B. Kostinski

Abstract A 2D video disdrometer (2DVD) probe was used to gather detailed drop measurements over a 770-min rain event. Accumulated totals of the rainfall and of the number of drops for each square centimeter showed persistent, significant correlated structures across the approximately 11 cm × 11 cm grid of the 2DVD. This is surprising because larger-scale studies suggest that the values in each square centimeter should be highly correlated with very little variation. Nevertheless, this correlation remains strikingly similar to what is observed at a coarser resolution, suggesting that it somehow scales with spatial resolution. However, because the correlation functions are not power laws, the origin of this scaling must be due to a factor other than fractal geometry. Analysis reveals that this occurs because of a filtering effect such that as the domain size (or resolution of a remote sensor) becomes finer, it is only the smaller wavelengths that contribute most to the variance so that the correlation function also scales. Consequently, correlated finescale structures can apparently occur even over 10 cm. This fine structure was also found for the kinetic energy and impact power of the rain, important for understanding the initiation of soil erosion. The patterns in the integrated parameters appeared to arise almost exclusively from patterns in the total number of drops with patterns in the drop sizes playing an insignificant role. Therefore, in future studies of rain it is recommended that the total number of drops be retained as a crucial variable.


1995 ◽  
Vol 41 (2) ◽  
pp. 191-201 ◽  
Author(s):  
Mazda A. Marvasti ◽  
Warren C. Strahle

Author(s):  
Sk Md Obaidullah ◽  
Chitrita Goswami ◽  
K. C. Santosh ◽  
Nibaran Das ◽  
Chayan Halder ◽  
...  

We present a novel approach for separating Indic scripts with ‘matra’, which is used as a precursor to advance and/or ease subsequent handwritten script identification in multi-script documents. In our study, among state-of-the-art features and classifiers, an optimized fractal geometry analysis and random forest are found to be the best performer to distinguish scripts with ‘matra’ from their counterparts. For validation, a total of 1204 document images are used, where two different scripts with ‘matra’: Bangla and Devanagari are considered as positive samples and the other two different scripts: Roman and Urdu are considered as negative samples. With this precursor, an overall script identification performance can be advanced by more than 5.13% in accuracy and 1.17 times faster in processing time as compared to conventional system.


2018 ◽  
Vol 21 (5) ◽  
pp. 965-972 ◽  
Author(s):  
Angelo Castello ◽  
Carlo Russo ◽  
Fabio Grizzi ◽  
Dorina Qehajaj ◽  
Egesta Lopci

Author(s):  
Bartłomiej Błaszczyszyn ◽  
Martin Haenggi ◽  
Paul Keeler ◽  
Sayandev Mukherjee

2002 ◽  
Author(s):  
J.M. Blackledge ◽  
A.K. Evans ◽  
M.J. Turner
Keyword(s):  

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