Abstract ArapidmethodofsettingchromatographicparametersforcalibrationofGC–MSwasintroduced.Bythis method,theinlettemperatureandtransmissiontemperaturewereallsetto280℃,anddefferentheatratewasselectedtochro- matographiccolumswithdefferentlenth(20,40℃/minfor15,30mcolum,repectivelyastestingoctafluoronaphthalene). ...
Bayesian artificial neural networks (BANNs) are trained with output from a GCM and used as emulators of the full model to allow a computationally efficient Markov Chain Monte Carlo (MCMC) sampling of the posterior for the GCM parameters calibrated against seasonal climatologies of temperature, ...
A few parameters were fitted to match the long-term (1973–2006) average country yields reported by FAO. These included: total heat units for crops to reach maturity (HEAT_UNITS); harvest index (HI_TARG) and biomass target (BIO_TARG), which allow control of biomass production by the ...
S/G lignin ratios have proven to be important parameters for gauging the recalcitrance of lignin, although no clear trend has been established as to whether or not a high S content results in increased monomeric sugar release following an enzymatic hydrolysis. The traditional methods for measuring ...
as unknown parameters, then too many parameters must be processed making the analytical systems more complex. In 1988, Lindberg and Kowalski [7] introduced a multivariate calibration method in a potentiometric titration for the analysis of mixtures of acids. This method takes advantage of a lot of...
Watershed-scale hydrologic models are used for a variety of applications from flood prediction, to drought analysis, to water quality assessments. A particular challenge in applying these models is calibration of the model parameters, many of which are difficult to measure at the watershed-scale. A...
Bayesian artificial neural networks (BANNs) are trained with output from a GCM and used as emulators of the full model to allow a computationally efficient Markov Chain Monte Carlo (MCMC) sampling of the posterior for the GCM parameters calibrated against seasonal climatologies of temperature, ...
The parameters of WASMOD-D model were optimized by using the multi-objective genetic algorithm (GA). In order to wane the influences of uncertainties which are rooted in GCMs, in addition to using various models, the biases in climatic parameters (precipitation and temperature) were corrected by...
With the same parameters, RiTHM was also forced with runoff from the LMD GCM. This induced an important degradation of the simulated hydrographs, regarding both volume and timing. It was largely explained by errors in precipitation, and more generally climate, in the GCM. The direct calibration...