Results 11 to 20 of about 587,894 (312)
Grape Yield Prediction Models: Approaching Different Machine Learning Algorithms
Horticulturae, 2023 Efficient marketing of winegrapes involves negotiating with potential buyers long before the harvest, when little is known about the expected vintage.
Caio Bustani Andrade +3 more
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The Effect of Sample Size and Data Numbering on Precision of Calibration Model to predict Soil Properties [PDF]
Journal of Agricultural Machinery, 2017 Introduction Precision agriculture (PA) is a technology that measures and manages within-field variability, such as physical and chemical properties of soil.
H Mohamadi-Monavar
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Quantification of Plant Root Species Composition in Peatlands Using FTIR Spectroscopy
Frontiers in Plant Science, 2020 Evidence of plant root biomass and production in peatlands at the level of species or plant functional type (PFT) is needed for defining ecosystem functioning and predicting its future development.
Petra Straková +8 more
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On the calibration of the 3/2 model [PDF]
European Journal of Operational Research, 2017 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Gudmundsson, Hilmar, Vyncke, David
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Italian Journal of Animal Science, 2021 The aim of this study was to develop near-infrared spectroscopy (NIRS) prediction models for the estimation of chemical components and the fibre undegradable fractions (uNDF) of hay-based total mixed rations (TMR).
Giovanni Buonaiuto +6 more
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Sensors, 2020 The performance of camera-based polarization sensors largely depends on the estimated model parameters obtained through calibration. Limited by manufacturing processes, the low extinction ratio and inconsistency of the polarizer can reduce the ...
Haonan Ren +4 more
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Statistical Inference in Calibrated Models [PDF]
Journal of Applied Econometrics, 1994 SUMMARY This paper describes a Monte Carlo procedure to assess the performance of calibrated dynamic general equilibrium models. The procedure formalizes the choice of parameters and the evaluation of the model and provides an efficient way to conduct a sensitivity analysis for perturbations of the parameters within a reasonable range.
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A simplified algorithm for leaky network analyzer calibration [PDF]
, 1995 A new algorithm for network analyzer calibration is presented. The error model includes leakage effects and can be applied to a general n-port NWA. The 2-port 16-term model becomes a special case of this new technique which is also hopefully suitable for
F. Sanpietro +2 more
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An Empirical Atmospheric Density Calibration Model Based on Long Short-Term Memory Neural Network
Atmosphere, 2021 The accuracy of the atmospheric mass density is one of the most important factors affecting the orbital precision of spacecraft at low Earth orbits (LEO). Although there are a number of empirical density models available to use in the orbit determination
Yan Zhang +3 more
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Optimal Transport for Model Calibration [PDF]
SSRN Electronic Journal, 2021 We provide a survey of recent results on model calibration by Optimal Transport. We present the general framework and then discuss the calibration of local, and local-stochastic, volatility models to European options, the joint VIX/SPX calibration problem as well as calibration to some path-dependent options.
Guo, I, Loeper, G, Obloj, J, Wang, S
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