Using Adaptive Response Surface Regression

Submission: The report from part 4 including all relevant graphs and numerical analysis along with interpretations.

The model parameters are estimated from the EP and therefore the AR can be calculated within the TP (Strong, 1992). Explicitly, the AR which

For the first five data point, the value of exponential model is close to the actual value. However, the exponential model didn’t work well for the

What is the goal in optimization? Find the decision variable values that result in the best objective function and 
satisfy all constraints.

(iv) Do the model estimates in (3.2) seem reasonable - or do the results provide evidence that it is a poor model? Explain. (2 marks)

To predict the behavior of a physical system governed by a complex mathematical model depends on un- derlying model parameters. For example, predicting the contaminant transport or oil production strongly influenced by subsurface properties, such as permeability, porosity and other spatial fields. These spatial fields are highly heterogeneous and vary over a rich hierarchy of scales, which makes the forward models

Our prediction model, the tenth period model, fitted the data especially well as illustrated below.

Optimization on the other hand refers to the application of methods to achieve selected goals mentioned above. In some perspectives, this process could involve both gaining of methods, example learning a new skill as well as the use of relevant behavior that one is very good at and use it the best way possible.

Equation 8 is the equation for the line of best fit generated by the graphing software with y equaling the absorbance and x the molarity. Equation 9 is equation 8 after solving for the missing variable x.

For the bottom-up approach uncertainty is less of a problem. The bottom-up approach does not depend

Simulation is a computer process that gives a probable NPV or IRR for a project. All factors that affect the project’s returns are input. The computer then randomly selects one observation from each category. All of the observations are combined and the NPV or IRR is calculated from those figures. Simulation gives a range of outcomes as well as the probability of the outcomes. It provides the total risk level of a project.

4. Sokolowski, John A. Principles of modeling and simulation: a multidisciplinary approach. Hoboken, NJ: Wiley, 2009. Print.

The objective function, decision variables and constraints are fed into solver to arrive at the optimal solution as shown in the below screenshot

adjusted prior to coupling the parts of the model together and running the simulation in steps 4

Chen {\it et al.} proposed a non-intrusive model reduction method based on black-box stencil interpolation method and machine learning method \cite{han2012}. Walton {\it et al.}proposed a non-intrusive reduced order technique for unsteady