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All the other methods are affected by problems such as the linearization of the right tail of the spectrum, and some of them are very demanding in data.
The aim of this work was first, to compare two methods for obtaining soil boundary-layer resistance, one based on the turbulent diffusion theory (TD) and another based on the energy balance of heated and unheated sensors (EB), and secondly, to analyse how the results obtained from both methods are affected by canopy structure parameters in typical sparse vegetation.
Typeability and accuracy of typing methods are affected by the distribution of CNS species and strains in different host species, and by the ability of test systems to incorporate information on new CNS species into their experimental design and reference database.
However, these methods are affected more easily by illumination changes.
However, all fitting methods are affected by the sudden shape change problem in GLD parameter estimation.
It can be observed that both the MZT and the CMT-MP-QP methods are affected severely by the desired signal look direction mismatch.
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The performance of most of these methods is affected by the frequency dependent attenuation of tissue, which causes mismatch of the receiver filter.
As a result, the efficacy of conventional localization methods is affected.
We then test how prediction accuracy of clustering transfer methods is affected by the number of clusters in all five personality traits.
We also evaluated how the performance of different methods was affected when different number of branches (3, 6, 9, and 12) per tree was sampled in estimating crown biomass.
It is obvious that the performance of all analytical methods is affected by various parameters investigated here.
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