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The proposed method is as fast as forward methods and as stable as backward methods.
Forward methods are known as fastest methods and backward methods are stable in any circumstances.
This paper discusses a number of backward and forward methods for inverse design.
Although this increases the amount of data to be transmitted, forward methods have the advantage of not requiring interaction between the encoder and the decoder.
Forward methods, such as the CFD-based adjoint method, CFD-based genetic algorithm method, and proper orthogonal decomposition method, show the promise in the inverse design of airflow and heat transfer in an enclosed environment.
An advantage of this methodology is that while forward methods are subject to region with loss of density of particles and hence loss of spatial resolution of the solution, the solution given by backward methods is given on any desired grid.
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Missing data were treated with the last observation carried forward method.
As noted above, missing data was replaced using the last observation carried forward method.
In the regression model, the Stepwise Forward method was used.
The forward method was used (adding variables one-by-one).
* Missing values imputed by last observed value carried forward method.
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