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First-order Minimisation Methods

The steepest descents method moves in the direction parallel to the net force, which in our geographical analogy corresponds to walking straight downhill. For 3N Cartesian coordinates this direction is most conveniently represented by a 3N-dimensional unit vector, sj. Thus  [Pg.262]

Fig 5 7 A line search is used to locate the minimum in the function in the direction of the gradient. [Pg.263]

The gradient at the minimum point obtained from the line search will be perpendicular to the previous direction. Thus, when the line search method is used to locate the minimum along the gradient then the next direction in the steepest descents algorithm will be orthogonal to the previous direction (i.e. gt -gjt-i =0). [Pg.263]

S A Teukolsky and tV T Vetterling 1992 Numerical Recipes in Fortran Cambridge, Cambridge University Press ) [Pg.263]

As the line search may itself be computationally demanding we could obtain the new coordinates by taking a step of arbitrary length along the gradient unit vector sj.. The new set of coordinates after step k would then be given by the equation  [Pg.264]


Equation 4 was discretised by a 5-point central difference formula and thereafter first-order differential equations 1, 2, 4 and 6 were solved by a backward difference method. Apparent reaction rate was solved by summing the average rates of each discretisation piece of equation 4. The reactor model was integrated in a FLOWBAT flowsheet simulator [12], which included a databank of thermodynamic properties as well as VLE calculation procedures and mathematical solvers. The parameter estimation was performed by minimising the sum of squares for errors in the mole fractions of naphthalene, tetralin and the sum of decalins. Octalins were excluded from the estimation because their content was low (<0.15 mol-%). Optimisation was done by the method of Levenberg-Marquard. [Pg.315]

When reflectance measurements are carried out on opaque or translucent food materials, a number of problems exist in the seleetion and preparation of the samples. The first is that simply by reason of its presentation method, the sample area as presented to the instrument may not be representative of the bulk of the material rmder test. Most instruments in common use are designed to accommodate samples whieh are flat, and therefore reflect light from one plane only. Most food materials are not flat and some degree of compromise has to be made in order to ereate viewing areas whieh are. It is often the case that it is advantageous to deliberately ehange the sitrface characteristics of the sample in order to enhanee eolom differenees between specimens. Andre and Pauli (1978), for example, pitlverised dehydrated pasta into a powder and then tabletted the powder for eolom measurement in order to minimise variation caused by differenees in the shapes and surfaee properties of commercially available produets. [Pg.93]

The separation of sugar nucleotides from such extracts is by no means easy, especially since it has to be as rapid as possible in order to minimise hydrolysis losses. Adsorption onto a basic ion-exchange resin is commonly used as a first step. It can be performed as a column method, as a batch extraction or, on a micro-scale, on sheets of ion-exchange materials. Considerable losses may occur on the resin. Elution can be by one of several different procedures, of which washing with ammonium chloride is one of the more useful (Recondo, Dankert and Passeron, 1965), since the salt is somewhat volatile. Other systems used include displacement by the chlorides of calcium, sodium or lithium, or by ammonium formate buffer. Hydrolysis losses are particularly likely with the last. [Pg.29]


See other pages where First-order Minimisation Methods is mentioned: [Pg.280]    [Pg.262]    [Pg.280]    [Pg.262]    [Pg.280]    [Pg.262]    [Pg.47]    [Pg.215]    [Pg.95]    [Pg.90]    [Pg.91]    [Pg.219]    [Pg.202]    [Pg.242]    [Pg.310]    [Pg.327]    [Pg.93]    [Pg.78]    [Pg.228]    [Pg.194]    [Pg.59]    [Pg.91]    [Pg.183]    [Pg.91]    [Pg.69]    [Pg.80]   


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Minimisation

Minimisation methods

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