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We analysed how the accuracy and uncertainty of calibrated seepage fluxes depend on the measurement interval of input data and on the accuracy and uncertainty of inferred local geohydrological parameters and boundary conditions.
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The hardness and elastic modulus of thin films reached the highest values of 16.5 and 148 GPa at 400 W and the surface morphology of the films did not suffer important changes in the interval of utilized input powers: RMS roughness decreased from 0.45 nm at 50 W to 0.20 nm at 400 W. All deposited films were transparent in the infrared range.
The actual probability can then be calculated by taking the integral of the function p(x) by the integration interval of the input variable x.
In this work, the variation interval of the input factors was defined over 4 orders of magnitude, 2 below and 2 above the reference value of each reaction constant (given in Table 3).
Note that the actual interval of the inputs of the P-point RFFT is Q.
Therefore, if we shift the inputs of an odd size P-point RFFT whose inputs have the pattern of x P [k]=x P [P−1−k] by (frac {P-1}{2}Q), the outputs will be (X_{P}[k]W_{N}^{frac {P-1}{2}Qk}), as the interval of the inputs is Q.
According to Eq. (6), we can get the relation of the outputs of the two (frac {P}{2} -point RFFTs as below (note the interval of the inputs is 2} -points case): X_{2}[k]=X_{1}[(-k)_{N}]times W^{-k2Q}, (15).
In the traditional approach of HAM transfer models, WDR is implemented in a simplified manner: the total mass of all raindrops impinging on a certain surface area of a building facade during the time interval of the meteorological input data (typically 1 h) is spatially and temporally averaged and is supplied to the facade as an averaged moisture flux.
Therefore, additional scenario analyses must be performed, for example by the extension of the range or the confidence interval of the clinical input variables, or the use of clinical probabilities from the overall study population in the clinical trials.
The input layer of five values that represent first input of the day number (one to five), second input of the time of the day (from 0 to 24 in 15 min interval), third input of the latitude of the IPP point (in radians), fourth input of the longitude of the IPP (in radians) and fifth input of the estimated Klobuchar model at same IPP point.
It might improve dynamic system models a standard time-series prediction, as the character of relative data allows to apply a wider range of input interval values than defined by the trained data.
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