prediction error
Influence of precision of emission characteristic parameters on model prediction error of VOCs/formaldehyde from dry building material.
... Errors in VOC/formaldehyde emission measurements result from three possible causes. One is the difference between the measurement methods used to determine the emission character- istic parameters, especially the initial ...
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Artificial neural networks compared with Bayesian generalized linear regression for leaf rust resistance prediction in Arabica coffee
... the prediction error rate. The proposed method has low prediction error rate and superior results when compared to those found by the Bayesian generalized ...
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Research article Computational analysis of the interaction between transcription factors and the predicted secreted proteome of the yeast
... the prediction error rate was ...decrease error rates and improve the chances of obtaining an actual extracellular protein in a given physiological ...The error reduction may come from the ...
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Dopamine, affordance and active inference.
... in prediction error shown in red (left middle ...between prediction units (black) and error units (red) that underlie the simulated reaching ...The prediction units encode conditional ...
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CMAME2016 101 formatted end
... responses’ prediction standard errors are not homogeneous. Prediction standard error ranges from ...responses’ prediction standard errors (relative magnitude of the prediction ...
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Combining structural modeling with ensemble machine learning to accurately predict protein fold stability and binding affinity effects upon mutation.
... We treat the stability prediction problem as an instance of the non-linear regression problem. Our model assumes as input a vector of 75 derived features (Table S1), some of which are only applicable for interface ...
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Matéria (Rio J.) vol.19 número4
... The annular die is utilized to manufacture nanofibers in the melt blowing process. The air flow field model of the annular die is established and solved numerically. Simulation results show the distributions of air ...
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Variable importance and prediction methods for longitudinal problems with missing variables.
... model versus one without the variable. Those based on procedures like LASSO are based on ar- bitrary statistical models (e.g., linear with main effects), so the model is likely to misspecified and thus the interpretation ...
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A simple ESR identification methodology for Electrolytic Capacitors conditon monitoring
... This paper presents a simple ESR identification methodology for electrolytic capacitors condition monitoring in view of preventive maintenance to signal the need of maintenance and or replacement. The identification ...
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Selection of an appropriately simple storm runoff model
... For each tested model structure, the number of free parameters was reduced in stages. The appropriate balance between simplicity and explanatory power was decided based on Aikake’s Final Prediction Error ...
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Daniel de Noronha Figueiredo Vieira da Cunha2 , José Carlos Pereira3 , Fabyano Fonseca e Silva4 , Oriel Fajardo de Campos5 , José Luis Braga6 , Janaina Azevedo Martuscello2
... square error goodness of fit ...square error and mean square prediction error goodness of fit measurements, the model by Wood (1967) was selected to represent the L2 subgroup because it showed ...
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Nearest template prediction: a single-sample-based flexible class prediction with confidence assessment.
... activation, prediction of disease phenotype and outcome, moni- toring of response to genetic or pharmacologic experimental perturbations ...in prediction of 2 or more classes beyond different assay ...
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Quantifying uncertainty in climatological fields from GPS radio occultation: an empirical-analytical error model
... geopotential height (the latter can be constructed using the dry pressure sampling er- ror in Eq. (9) together with the dry temperature and some standard gravity value like 9.8 m s −2 as sufficient proxies to estimate ...
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Comparing two versions of a non-linear model for simulating leaf number and developmental stages in maize based on air temperature
... an error varying from +8 to -21 days and from 0 to -7 days with the WE Tmean and WE Tmm models, ...an error of two and seven days with the WE Tmm model, and eight and 21 days with the WE Tmean model, ...
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Rev. Adm. (São Paulo) vol.52 número1
... Prediction models are widely used in both business and pub- lic sectors. They are useful either for planning as for sensitivity analysis, as to the environmental changes for effective deci- sion making. Thus there ...
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Haplotype reconstruction error as a classical misclassification problem: introducing sensitivity and specificity as error measures.
... possible error due to the no-LD ...these error rates remain unmatched in real data ...the error rate derived from simulations instead of using the analytical approach was practically the same, but ...
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Reliable Dynamic Voltage Scaling for Real-Time Systems with Uncertain Execution Time and Resource Constraints
... a) Error recovery: Error recovery can be achieved by either forward or backward error recovery. The second strategy, fault treatment, aims to prevent activation of faults and so action [r] ...
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Assessment of the Level-3 MODIS daily aerosol optical depth in the context of surface solar radiation and numerical weather modeling
... 2 product. However, for larger AOD values, higher errors are found. Consequently, we propose new functions for the expected error of the Level-3 AOD, as well as for both its mean error and its standard ...
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Biosignals learning and synthesis using deep neural networks
... high prediction rates while estimat- ing the sequence of time-series data, in several fields, without the input of an extensive amount of features, nor their ...
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