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The most effective variable on local scour depth at pile groups was determined using different sets of input combinations.
The ultrasonic amplitude and adsorbent mass were found to be the most effective variable influencing the adsorption process.
The ultrasonic amplitude was found to be the most effective variable influencing the devulcanization process and mechanical properties.
This requires both an effective variable selection process and a validation technique to assess the predictive performance of the derived models.
It can be seen from Fig. 3b that dynamic time was not very effective variable in the range of 2 6 min for solubility experiments.
Response surface analysis revealed that the data were adequately fitted to a second-order polynomial model with R2 0.9665 and the most effective variable was pressure (P ≤ 0.05).
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However, the models were implemented for the construction of 3D response surface plots from the ANN and RSM models in order to show the most effective variables as well as the effects of their interaction on the research octane number.
However, the variables preselected based on the calibration set might not be representative of the effective variables in future prediction process due to the large variability among soil sample sets.
The design with four effective variables (Table 2) was run by the design-expert version 8.0.7.1.
The most effective variables were found as pressure and co-solvent ratio (p < 0.005).
All effective variables on the extraction efficiency of the analytes were optimized.
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CEO of Professional Science Editing for Scientists @ prosciediting.com