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Map of the data recording zone.
Fig. 3. Station map of the data used in this study.
For example, it provides a map of the data structures in memory.
Fig. 7 (a) random noise with amplitude equal to 0.07% of the maximum data amplitude was added to the gravity data set shown in Fig. 6(a), (b) NSTD map of the data in (a), (c) Edge map of the data in (a) obtained by the proposed edge operators.
Fig. 4 (a) random noise with amplitude equal to 0.07% of the maximum data amplitude was added to the gravity data set shown in Fig. Fig. 3(a), (b) NSTD map of the data in (a), (c) Edge map of the data in (a) obtained by the proposed edge operators.
We also describe the uncertainty and correlation calculations performed, provide a map of the data flow through the program, and present representative examples of PMF profiles calculated using OFR-AT.
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Coloured geochemical maps of the data subset were drawn using the ESRI ArcMap 10.2 software package.
The correlation coefficient obtained between the predicted and training data set is 0.9657, indicating an accurate mapping of the data.
A hierarchical algorithm can be viewed as a mapping of the data proximity matrix into a cophenetic matrix.
Another limitation of our approach is that it relies on a good mapping of the data into 3D space.
The correlation coefficient obtained between the predicted and training dataset is 0.9889, which is very close to 1, indicating an accurate mapping of the data.
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