Deterministic procedure

For quantitative determination, the semi-deterministic procedure needs to use both a reference spectra basis and the corresponding calibration files (see Chapters 2 and 4). The value of nitrate concentration can then be calculated using the following relation ... 

It must be emphasized that a risk-based approach requires a number of conventions, just as the deterministic procedure does. Hence, we are dealing with conventions which enable one to treat generally occurring cases such as... 

Monte Carlo methods are perhaps the most frequently used in computational statistical mechanics. In particular, the Metropolis Monte Carlo technique has been used extensively in simulation of liquids. Monte Carlo methods are probabilistic, rather than deterministic, procedures atoms are moved more or less randomly during the course of the simulation. In a Metropolis Monte Carlo simulation of a molecular system, the following steps would be followed ... 

Unlike Monte Carlo, MD is a deterministic procedure. Atoms move according to the laws of Newtonian mechanics. An MD simulation is performed by integrating Newton s equations of motion over time for the molecular system. 

The architecture of SYNAPSE is very obvious from the technical details of the underlying synthesis mechanism (see Chapters 12 and 13) synthesis is achieved by a sequence of 7 non-deterministic procedures, each implementing one of the 7 synthesis steps. The implementation is actually based on version 4 of the divide-and-conquer schema, unlike the presentation in this book, which is restricted to version 3. This means that arbitrary A2-ary predicates can be handled, rather than only binary ones. 

The component fragihties are evaluated on a probabilistic basis, but a preliminary screening of the high confidence of low probability of failure (HCLPf) value may turn their evaluation into a simplified equivalent deterministic procedure ... 

Standard procedures that are used for testing of construction materials are based on square pulse actions or their various combinations. For example, small cyclic loads are used for forecast of durability and failure of materials. It is possible to apply analytical description of various types of loads as IN actions in time and frequency domains and use them as analytical deterministic models. Noise N(t) action as a rule is represented by stochastic model. 

The word deterministic" means that the model employs a specific surface geometry or prescribed roughness data as an input of the numerical procedure for solving the governing equations. The method was originally adopted in micro-EHL to predict local film thickness and pressure distributions over individual asperities, and it can be used to solve the mixed lubrication problems when properly combined with the solutions of asperity contacts. 

Depending on whether or not stochastic features are introduced in the simulation procedure, simulation methods are sometimes classified as stochastic or deterministic. Although the second term is usually applied to methods related to the numerical solution of Newton s equations, the first term is applied to a wide variety of simulation metfiods. 

Ideally, any procedure for signal enhancement should be preceded by a characterization of the noise and the deterministic part of the signal. Spectrum (a) in Fig. 40.18 is the power spectrum of white noise which contains all frequencies with approximately the same power. Examples of white noise are shot noise in photomultiplier tubes and thermal noise occurring in resistors. In spectrum (b), the power (and thus the magnitude of the Fourier coefficients) is inversely proportional to the frequency (amplitude 1/v). This type of noise is often called 1//... 

Here, 7 is the friction coefficient and Si is a Gaussian random force uncorrelated in time satisfying the fluctuation dissipation theorem, (Si(0)S (t)) = 2mrykBT6(t) [21], where 6(t) is the Dirac delta function. The random force is thought to stem from fast and uncorrelated collisions of the particle with solvent atoms. The above equation of motion, often used to describe the dynamics of particles immersed in a solvent, can be solved numerically in small time steps, a procedure called Brownian dynamics [22], Each Brownian dynamics step consists of a deterministic part depending on the force derived from the potential energy and a random displacement SqR caused by the integrated effect of the random force... 

The procedures discussed so far take as fundamental variables the species concentration and specific rates, the latter obtained from homogeneous experiments. Such procedures are called deterministic—that is, admitting no fluctuation in the number of reactant species—as opposed to stochastic methods where statistical variation is built in. 

We have investigated another procedure for reducing the computational expense of the AIMS method, which capitalizes on the temporal nonlocality of the Schrodinger equation and the deterministic aspect of the AIMS method. Recall that apart from the Monte Carlo procedure that we employ for selecting initial conditions, the prescription for basis set propagation and expansion is deterministic. We emphasize the deterministic aspect because the time-displaced procedure relies on this property. 

In most natural situations, physical and chemical parameters are not defined by a unique deterministic value. Due to our limited comprehension of the natural processes and imperfect analytical procedures (notwithstanding the interaction of the measurement itself with the process investigated), measurements of concentrations, isotopic ratios and other geochemical parameters must be considered as samples taken from an infinite reservoir or population of attainable values. Defining random variables in a rigorous way would require a rather lengthy development of probability spaces and the measure theory which is beyond the scope of this book. For that purpose, the reader is referred to any of the many excellent standard textbooks on probability and statistics (e.g., Hamilton, 1964 Hoel et al., 1971 Lloyd, 1980 Papoulis, 1984 Dudewicz and Mishra, 1988). For most practical purposes, the statistical analysis of geochemical parameters will be restricted to the field of continuous random variables. 

The sensitivity analysis of a system of chemical reactions consist of the problem of determining the effect of uncertainties in parameters and initial conditions on the solution of a set of ordinary differential equations [22, 23], Sensitivity analysis procedures may be classified as deterministic or stochastic in nature. The interpretation of system sensitivities in terms of first-order elementary sensitivity coefficients is called a local sensitivity analysis and typifies the deterministic approach to sensitivity analysis. Here, the first-order elementary sensitivity coefficient is defined as the gradient... 

So far, only techniques, starting from some initial point and searching locally for an optimum, have been discussed. However, most optimization problems of interest will have the complication of multiple local optima. Stochastic search procedures (cf Section 4.4.4.1) attempt to overcome this problem. Deterministic approaches have to rely on rigorous sampling techniques for the initial configuration and repeated application of the local search method to reliably provide solutions that are reasonably close to globally optimal solutions. 

It approximates the expectation of the stochastic formulation (usually called the true problem) and can be solved using deterministic algorithms. Problem (9.19) can be solved iteratively in order to provide statistical bounds on the optimality gap of the objective function value. The iterative SAA procedure steps are explained in Section 7.5 of Chapter 7. 

Dynamic aibcation is an alternative procedure in which the allocation of treatment to a subject is influenced by the current balance of allocated treatments and, in a stratified trial, by the stratum to which the subject belongs and the balance within that stratum. Deterministic dynamic allocation procedures should be avoided and an appropriate element of randomisation should be incorporated for each treatment allocation. ... 

Since a number of particles involved in any reaction event are small, a change in concentration is of the order of 1 /V. Therefore, we can use for the system with complete particle mixing the asymptotic expansion in this small parameter 1 /V. The corresponding van Kampen [73, 74] procedure (see also [27, 75]) permits us to formulate simple rules for deriving the Fokker-Planck or stochastic differential equations, asymptotically equivalent to the initial master equation (2.2.37). It allows us also to obtain coefficients Gij in the stochastic differential equation (2.2.2) thus liquidating their uncertainty and strengthening the relation between the deterministic description of motion and density fluctuations. 

---