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The major advantages of ANN compared to RSM are (1) it does not need a prior specification of appropriate fitting function and (2) ANN is capable of universal estimation, i.e., ANN can estimate nearly all types of nonlinear functions such as quadratic functions, where RSM is suitable only for quadratic estimations [9].
The goal of this research work is to develop a useful and universal estimation procedure to determine simultaneously the kinetic parameters involved in the chemical modelling under study such as combustion, pyrolysis, waste stabilization, etc.
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Under the assumption of one-bit message from nodes to fusion node, universal decentralized estimation schemes were investigated [6] and distributed estimators were derived for pragmatic signal models [7].
Asner et al. (2011) developed a simple universal forest carbon estimation method for tropical forests that reduces the amount of required field measurements.
Our objectives were to develop a universal surgical risk estimation tool, to compare performance of the universal vs previous procedure-specific surgical risk calculators, and to allow surgeons to empirically adjust the estimates of risk.
The drqPCR is a universal strategy for estimation of ratios directly in the sample, alleviating the need for control samples and therefore ideal for analysis of unpaired samples.
Nonlinear modeling, universal methods, and order estimation are advanced topics that are also considered.
This paper presents an universal tool for the estimation of maximum subsidence (SMax).
Accordingly, a new universal correlation for the estimation of D⁎ as function of residual entropy and r was obtained, giving rise to an average absolute relative deviation of 9.13% for all database.
We introduce a universal Langmuir model for estimation of absolute target concentration from microarray experiments.
The universal kriging variance incorporates trend estimation error as well as spatial interpolation error.
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