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Fig. 2 Opportunity geological grid model The formula (13) gives the logical control of the opportunity geological grid.
For this prediction model the formula eβ0+c+ β1X1+…βkXk / 1 + e β0+c+ β1X1+…βkXk was used, whereas β was deduced from the multivariate regression analysis as shown in Table 5.
Recall that for the proportional hazards model, the formula relating a covariate x1 to the hazard h(t) at time t is where h0 t) is the baseline hazard.
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Finally, based on the power-function model, the formulae for predicting the M-Ф curves of the joints were established.
Using a sand deposition model, the formulas of dynamic angle of repose [e.g., Eqs.(11), (12)] for different conditions were obtained.
"In a market like China, everyone should try to create new models". The formula is apparently working.
"For most machine learning models, the formula is so big it would take more than a page to write it down," Rudin said.
As social networking companies continue to experiment with business models, the formula will be different for each one, Wharton faculty say.
In this setting, a cubic model with the formula (1.1305 × OD)+(−0.6712 × OD) +(0.1624 × OD) was the optimal model to fit the standards (RSQ=0.981).
However, the model using the formula proposed by Eurocode 4 or neglecting the slab spatial composite effect may give unsatisfactory predictions.
LPS-concentrations were determined by calculating a standard curve using a 4-parameter logistic non-linear regression model utilizing the formula y = (A − D /[1 + (X/C B] + D.
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