Goal of modeling

The final goal of models used for testing or screening is to verify whether a special condition or feature is present or not. In this case the model system should be selected a priori based on scientific consensus and the testing protocols must be standardized in order to obtain comparable values when the same test is performed by two different laboratories or operators. Moreover, the existence of standardized methodologies could be very useful for regulators which need a certain degree of reliability to make appropriated decisions. 

Very rarely are measurements themselves of much use or of great interest. The statement "the absorption of the solution increased from 0.6 to 0.9 in ten minutes", is of much less use than the statement, "the reaction has a half-life of 900 sec". The goal of model-based analysis methods presented in this chapter is to facilitate the above translation from original data to useful chemical information. The result of a model-based analysis is a set of values for the parameters that quantitatively describe the measurement, ideally within the limits of experimental noise. The most important prerequisite is the model, the physical-chemical, or other, description of the process under investigation. An example helps clarify the statement. The measurement is a series of absorption spectra of a reaction solution the spectra are recorded as a function of time. The model is a second order reaction A+B->C. The parameter of interest is the rate constant of the reaction. 

The form of the response function to be fitted depends on the goal of modeling, and the amount of available theoretical and experimental information. If we simply want to avoid interpolation in extensive tables or to store and use less numerical data, the model may be a convenient class of functions such as polynomials. In many applications, however, the model is based an theoretical relationships that govern the system, and its parameters have some well defined physical meaning. A model coming from the underlying theory is, however, not necessarily the best response function in parameter estimation, since the limited amount of data may be insufficient to find the parameters with any reasonable accuracy. In such cases simplified models may be preferable, and with the problem of simplifying a nonlinear model we leave the relatively safe waters of mathematical statistics at once. 

Although prediction is often considered to be the ultimate goal of modeling, it is neither the only nor the most crucial one. In fact, the above example of Henry s law is a highly idealistic one. For instance, it precludes the existence of contradictory information. We know that real life is different for two major reasons. First, observations bear uncertainties which are linked to various factors, such as the limited precision of our analytical tools. Quantum mechanics yields an insurmountable theoretical reason for why we cannot make an absolutely precise observation. But we don t even have to invoke the uncertainty principle. We can just argue that data are never absolutely exact. 

The goal of model building is to produce a polymer chain that... 

These laws, which in various forms are active and being upheld in courts today, have two implications. The first is that servers of alcohol, whether a bartender or the host of a private dinner party, can in some circumstances be held liable for the actions of intoxicated patrons or guests. The second implication, important in the context of prevention, is that servers and hosts can contribute to preventing alcohol-related problems through their decisions not to serve alcohol to persons who are intoxicated. Indeed, the goal of model legislation for a uniform dram shop law is the prevention of alcohol-related injuries, deaths, and other damages (Mosher Colman, 1986),... 

Pottinger and Bernstein [2003] and Rondo [Melnik et al. 2003] both describe merge operators for Model Management [Bernstein et al. 2000], The goal of Model... 

First, the model or thermodynamic system will virtually always be incomplete and inaccurate to some degree. The reasons for this have largely to do with the choice and quality of the data used by the model. This will be discussed in more detail in later sections (e.g., 4.1). The goal of modeling could be said to be to minimize this degree of incompleteness and inaccuracy. 

Our knowledge of some geochemical systems is decidedly better than others. Therefore, the lack of reaction properties may be a prohibitive problem for one chemical system, but not for another where the contaminant of concern is different. Thus, what types and what models are used depends on the goals of modeling. 

As mentioned above, the system parameters are unknown and constant. One of the primary goals of modeling is to estimate the system parameters. The fact that they are unknown distinguishes them from independent variables or covariates. Note that by this definition, a variable in a model equation may be a parameter in one analysis and an independent variable... 

Although only relative energies are needed for an analysis of a pressure-dependent reaction system, the final goal of modelers is to incorporate these results into a reaction mechanism and perform simulations. In this case thermodynamic data of all species are needed, so we need to convert the absolute electronic energies to heats of formation. Two conversion methods are widely used (1) atomization energies [66 8] and (2) isodesmic reactions [68,69]. The atomization method is based on the decomposition of a species into its atoms. For a species this reaction is... 

In summary, the current 3D model of the mouse lens is a first step towards implantation of human lens models and prediction and investigation of lens pathologies. The ultimate goal of modeling the fluid dynamics in the ocular lens is to create a comprehensive computational model of the fluid dynamics of the human eye. Such system linked with the models from the rest of the body (e.g. blood pressure and sugar level models) can lead to an extensive model of the human body, which can be used by students and scientist to investigate the links between these phenomena and eye pathologies such as cataracts. 

The principal goals of modeling the fire behavior of structural composites are ... 

The goal of model calibration is to seek an optimal solution for the reactor model to match the real operation, and there is no single and best solution. It is important to assign reasonable tolerance into the objective functions and loose some of them when necessary. 

WertherJ, Heinrich S, Dosta M, Hartge E-U The ultimate goal of modeling—simulation of system and plant performance, Particuology 9 320—329, 2011. 

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