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Algorithm, validity

COMPOSITIONS OF THE EXTRACTION LIQUIDS USED FOR THE ALGORITHM VALIDATION EXPERIMENT AND FOR THE MODELLING OF THE EXTRACTION OF A NUMBER OF SULPHONAMIDES... [Pg.285]

Data Processing derived values, data conversions, scaling, frequencies, periods, calculations, algorithms, validity checks, error correction... [Pg.208]

Expanding the proportional terms using P(t) = ke(t) and the integral term using the Euler integration algorithm valid for small time intervals. At = t - t -i ... [Pg.376]

Alternate projection methods aim to reduce the data dimensionality by optimizing the representation in the lower-dimension space so that the distances between points in the projected space are as similar as possible to the distances between the corresponding points in the original space. We will describe here a class of methods known as multidimensional scaling (MDS). The aim of these methods is to project data from a pseudo-metric space (i.e., one characterized by a dissimilarity measure) onto a metric space. Such methods are especially useful for preprocessing non-metric data in order to use algorithms valid only for metric input. [Pg.253]

A novel optimization approach based on the Newton-Kantorovich iterative scheme applied to the Riccati equation describing the reflection from the inhomogeneous half-space was proposed recently [7]. The method works well with complicated highly contrasted dielectric profiles and retains stability with respect to the noise in the input data. However, this algorithm like others needs the measurement data to be given in a broad frequency band. In this work, the method is improved to be valid for the input data obtained in an essentially restricted frequency band, i.e. when both low and high frequency data are not available. This... [Pg.127]

Iteration of the steps, descriptor selection, model building, and model validation in combination with an optimi ation algorithm allows one to select a descriptor subset having maximum predictivity. [Pg.402]

Jones G, P Willett, R C Glen, A R Leach and R Taylor 1997. Development and Validation of a Geneti Algorithm for Flexible Docking. Journal of Molecular Biology 267 727-748. [Pg.739]

If the magnitudes of the dissipative force, random noise, or the time step are too large, the modified velocity Verlet algorithm will not correctly integrate the equations of motion and thus give incorrect results. The values that are valid depend on the particle sizes being used. A system of reduced units can be defined in which these limits remain constant. [Pg.274]

Validation and Application. VaUdated CFD examples are emerging (30) as are examples of limitations and misappHcations (31). ReaUsm depends on the adequacy of the physical and chemical representations, the scale of resolution for the appHcation, numerical accuracy of the solution algorithms, and skills appHed in execution. Data are available on performance characteristics of industrial furnaces and gas turbines systems operating with turbulent diffusion flames have been studied for simple two-dimensional geometries and selected conditions (32). Turbulent diffusion flames are produced when fuel and air are injected separately into the reactor. Second-order and infinitely fast reactions coupled with mixing have been analyzed with the k—Z model to describe the macromixing process. [Pg.513]

Rectification accounts for systematic measurement error. During rectification, measurements that are systematically in error are identified and discarded. Rectification can be done either cyclically or simultaneously with reconciliation, and either intuitively or algorithmically. Simple methods such as data validation and complicated methods using various statistical tests can be used to identify the presence of large systematic (gross) errors in the measurements. Coupled with successive elimination and addition, the measurements with the errors can be identified and discarded. No method is completely reliable. Plant-performance analysts must recognize that rectification is approximate, at best. Frequently, systematic errors go unnoticed, and some bias is likely in the adjusted measurements. [Pg.2549]

Many sophisticated models and correlations have been developed for consequence analysis. Millions of dollars have been spent researching the effects of exposure to toxic materials on the health of animals the effects are extrapolated to predict effects on human health. A considerable empirical database exists on the effects of fires and explosions on structures and equipment. And large, sophisticated experiments are sometimes performed to validate computer algorithms for predicting the atmospheric dispersion of toxic materials. All of these resources can be used to help predict the consequences of accidents. But, you should only perform those consequence analysis steps needed to provide the information required for decision making. [Pg.34]

Validate, or otherwise, using a gene tie algorithm that this value of K maximizes the fitness funetion... [Pg.379]

The number of neurons to be used in the input/output layer are based on the number of input/output variables to be considered in the model. However, no algorithms are available for selecting a network structure or the number of hidden nodes. Zurada [16] has discussed several heuristic based techniques for this purpose. One hidden layer is more than sufficient for most problems. The number of neurons in the hidden layer neuron was selected by a trial-and-error procedure by monitoring the sum-of-squared error progression of the validation data set used during training. Details about this proce-... [Pg.3]

Numerical accuracy and efficiency are critical issues for the DML model to be accepted in engineering applications. FFT-based algorithm has been introduced to speed up the computations, and attempts have been made to validate the model by comparing the results from the present DML model with those from other sources of numerical analyses and experiments. [Pg.144]

Statistical and algebraic methods, too, can be classed as either rugged or not they are rugged when algorithms are chosen that on repetition of the experiment do not get derailed by the random analytical error inherent in every measurement,i° 433 is, when similar coefficients are found for the mathematical model, and equivalent conclusions are drawn. Obviously, the choice of the fitted model plays a pivotal role. If a model is to be fitted by means of an iterative algorithm, the initial guess for the coefficients should not be too critical. In a simple calculation a combination of numbers and truncation errors might lead to a division by zero and crash the computer. If the data evaluation scheme is such that errors of this type could occur, the validation plan must make provisions to test this aspect. [Pg.146]

In both cases 1 — rS < 1 and, therefore, for a solution of problem (15)-(16) estimate (14) is valid, but r > 2/A. Because of rounding errors, the computational process is unstable for large j the growth of its solution causes abnormal termination in the computer realization of the algorithm. [Pg.94]

This equation has been derived as a model amplitude equation in several contexts, from the flow of thin fluid films down an inclined plane to the development of instabilities on flame fronts and pattern formation in reaction-diffusion systems we will not discuss here the validity of the K-S as a model of the above physicochemical processes (see (5) and references therein). Extensive theoretical and numerical work on several versions of the K-S has been performed by many researchers (2). One of the main reasons is the rich patterns of dynamic behavior and transitions that this model exhibits even in one spatial dimension. This makes it a testing ground for methods and algorithms for the study and analysis of complex dynamics. Another reason is the recent theory of Inertial Manifolds, through which it can be shown that the K-S is strictly equivalent to a low dimensional dynamical system (a set of Ordinary Differentia Equations) (6). The dimension of this set of course varies as the parameter a varies. This implies that the various bifurcations of the solutions of the K-S as well as the chaotic dynamics associated with them can be predicted by low-dimensional sets of ODEs. It is interesting that the Inertial Manifold Theory provides an algorithmic approach for the construction of this set of ODEs. [Pg.285]


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See also in sourсe #XX -- [ Pg.4 ]




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