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This chapter presents a discussion of the principles and techniques for modeling water consumption and reuse, including how to handle complexity and to ensure model adequacy and sufficient precision.
The residual analysis is performed to check for model adequacy and assumptions.
To confirm the used model adequacy and the validity of the resulted optimization conditions, additional experiment was performed under optimal operating conditions.
In order to confirm the model adequacy and the validity of the optimization procedure, experiments were performed in six real contaminated soils samples.
Validation was carried out through model adequacy and specificity tests, limits of quantification and detection determination, and full uncertainty assessment on the whole analytical method.
The statistical optimization approach usually involves various steps like designing the experiments with defined levels and factors, executing the statistically intended experimental trials, assessing the factors of the ideal terms, expecting the responses, analysis of variance (ANOVA), checking model adequacy and validation of the obtained model (Diwaniyan et al. 2012).
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The residuals from the least squares fit played an important role in judging model adequacy (Myers and Montgomery 2002).
Various analyses such as ANOVA, model adequacy check and numerical optimisation were performed to validate the predicted optimal model.
The details of model development and model adequacy test by analysis of variance (ANOVA) are presented in this paper.
Violations of the basic assumptions and model adequacy can be easily investigated by the examination of residuals.
This method was efficient; only 20 experiments were necessary to assess these conditions and model adequacy was very satisfactory, as the coefficient of determination was 0.9560.
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