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The NN effort with the integration of GIS in the study is not a function approximation problem, thus it can not estimate shear wave velocity (Vs), as well as site classification.
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Finally, the ground water quality (GWQI) map was generated using GWQI values (throughout geographic coordinate as an agent for distinguishing geographic coordinate) and GIS capabilities in the study area.
Efficacy results of alosetron on the IBS global improvement scale (GIS) in this study have been previously published.
In GIS, the study area was separated to raster format in the pixel dimensions of 1 km and also by incorporation of input data layers of the Fuzzy Network-CANFIS model; the geo-referenced layers of the effective factors in groundwater quality were earned.
We constructed the study area map with spatial distribution of households in the study areas by using ArcView GIS V.3.2 (ArcGIS, ESRI, Redlands, California, USA).
A number of studies on the hydrogeochemistry of Mumbai have been conducted (cf. Naik et al. 2007; Tirumalesh et al. 2010; Kamble and Vijay 2011) and the use of GIS in such studies explored (Anbazhagan and Nair 2004; Shankar and Mohan 2006).
GIS capabilities are applied to refine the results, adding traffic network in the study.
The eight EU habitats present in the study area were surveyed and mapped using GIS.
GIS has been applied to visualize the spatial distribution of groundwater quality in the study area.
Table 4 shows the p-values for the three different effects in the study: group or sequence (SOVAT → SPSS-GIS, or SPSS-GIS→ SOVAT), period (period 1, period 2), and intervention (SOVAT, SPSS-GIS).
Only when GIS are combined with spatial analytical methods can the result provide a helpful tool in the study of public health issues [ 9, 10].
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