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The first stage modelling process, which used a random parameters logit model with error components, suggested that willingness to pay was higher for increasing the abundance of native bird than for non-bird species.
In this study, we locate their change-points by formulating the HP filter as a generalized unobserved components model with error terms of mixtures of normal distributions.
The results of ANFIS model with error indices including coefficient of determination value of 0.97 and root mean square error value of 0.03 was so suitable.
In this paper, an extreme learning machine model with error correction with higher efficiency is developed to predict power output of a wind farm in a ultra-short-term time scale.
A high tensile shear failure load value of 3850 N and low interface hardness value of HV 81 was observed for joints made under optimum conditions, and validation experiments confirmed the high predictability of the developed model with error less than 2%.
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Results demonstrate the good behaviour of the model, with errors below 0.15 °C in target temperature estimates.
The yields of all crops have been predicted by the model with errors ranging from 8.4% (winter wheat) to 12.1% (maize).
Here, we take a similar approach as that of Fonseca et al. (2008) in that we assume a linear model with errors that may have a heavy tail distribution.
We did not employ other model selection techniques as we assumed a linear model with errors normally distributed.
MSMB's internal model representation allows saving a model with errors and inconsistencies (e.g., an undefined function argument; a syntactically malformed reaction).
LSA-based DS modeling with error awareness is also beneficial for DS detection.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.
Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com