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The relationship between the operating variables and PS and PSD of the prepared samples can be constructed by an ANN modeling approach.
Response surface methodology (RSM) revealed the effects of interaction between the operating variables, which would not have been identified by the traditional "one-factor-at-a-time" method.
The relationship between the operating variables and the sizes of primary particles reveals that the nature of this polymer is the dominant factor on its solid-state engineering in the course of its precipitation.
The main goal of the current work is to categorize some unknown samples, using discrimination function analysis between the operating variables and powder properties.
Its main objective is to categorize unknown samples using analysis of discrimination function between the operating variables and powder properties in two or more naturally occurring groups.
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A broad range of organic loading rate between 10 and 60 g COD L−1 d−1 was used as the operating variables.
Next, an ANN-based process model was developed for approximating the non-linear relationship between the fermentation operating variables and the EPS yield.
The individual effects, as well as the interactions between operating variables, are investigated by using an experimental design methodology.
A central composite design (CCD) with response surface methodology (RSM) is applied to evaluate the relationships between operating variables, such as TiO2 and Fenton dosage, pH, and reaction time, to identify the optimum operating conditions.
A central composite design (CCD) with response surface methodology (RSM) was applied to evaluate the relationships between operating variables, such as ozone and persulfate dosages, pH, and reaction time, to identify the optimum operating conditions.
They utilized CCD and RSM to establish the relationship between operating variables (dosage and pH) and leachate parameters removal.
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