28 results were found for WA 0821 1305 0400 Kontraktor Pagar Minimalis Ideal Cibodas Kota Tangerang.

Results:

• 21. Bardarbunga-2014_August-events

  /media/jar/Bardarbunga-2014_August-events.pdf

• 22. Bárðarbunga 2014 - August events

  /earthquakes-and-volcanism/articles/nr/3000/

• 23. 2013_001_Nawri_et_al

  the validity of the ideal gas law, hydrostatic balance, a piecewise linear vertical gradient of air temperature, and neglecting the effects of water vapour. Pressure, p, as a function of height can then be derived through vertical integration of the hydrostatic balance equation, and is given by p(h(x;y);z) = p0 exp g R Z h(x;y)+z 0 dx T (x ) ; (5) where p0 is pressure at mean sea level, T /media/vedurstofan/utgafa/skyrslur/2013/2013_001_Nawri_et_al.pdf

• 24. 2012-Refsgaard_etal-uncertainty_climate-change-adaptation-MITI343

  backgrounds, scientific disciplines, value systems and interests. The level of uncertainty characterises how well the uncertainty can be described within the range from determinism to total ignorance (Fig. 1), where determinism is the ideal, non- achievable, situation where everything is known exactly and with absolute certainty. Within this range, statistical uncertainty can be described using well /media/loftslag/2012-Refsgaard_etal-uncertainty_climate-change-adaptation-MITI343.pdf

• 25. Moellenkampetal_etal-2010

  /media/loftslag/Moellenkampetal_etal-2010.pdf

• 26. VanderKeur_etal-2008-Uncertainty_IWRM-WARM

  and with absolute certainty, an ideal that is never achieved in policy relevant sciences due to the complexity of the problem dealt with (Krayer von Krauss 2005). In this range, statistical uncertainty can be described in statistical terms, e.g. measurement error due to sampling error, inaccuracy or imprecision. In contrast, scenario uncertainty cannot be described statistically. Scenarios are common /media/loftslag/VanderKeur_etal-2008-Uncertainty_IWRM-WARM.pdf

• 27. VI_2020_008

  when setting up the Peak-over-Threshold model is to select a threshold that is large enough not to violate the basis of the GP distribution, but low enough so that enough data are extracted from the original timeseries. Several methods exist to determine the ideal threshold for a timeseries, often done manually (e.g. Coles, 2001). This is not possible when dealing with a large set of timeseries /media/vedurstofan-utgafa-2020/VI_2020_008.pdf

• 28. VI_2020_005

  /media/vedurstofan-utgafa-2020/VI_2020_005.pdf