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By golden section

The optimum seeking methods which have been found to be particularly useful are the modified Fibonacci search (search by golden section) for one-dimensional searches and the Hooke-Jeeves search for multi-dimensional searches. Beveridge and Schechter (8) give a complete description of these searches. [Pg.100]

EX221 2.2.1 Optimum dosing by golden section method M25... [Pg.15]

Example 2.2.1 Optimal drug dosing by golden section search... [Pg.91]

REM EX. 2.2.1 OPTIMUM DOSINE BY GOLDEN SECTION METHOD 104 REM MERGE M25... [Pg.94]

The teeth of a comb are not really a very important item in life. Nobody ever cared to consider a comb from such an angle.. .. It could also be compared to a golden section, when you have a different [proportionate] relation of length to lines. That s very farfetched, but I am always attracted by the farfetched.. . . The comb becomes [a metaphor of] the generation of space, space generated by [the number and width of] the teeth.. . . There is a possibility, as I said, of generating space from a flat surface. You can do it with any surface. ... [Pg.231]

Parabolic interpolation is more effective than golden section search for this problem, because the function is of parabolic character in the vicinity of the minimum. To show a counterexample we slightly change the approximate objective function (2.19) and define by... [Pg.98]

The only parameter that has been fixed in the above three sequential stages is the HRAT. We can subsequently update the H RAT by performing a one-dimensional search using the golden section search method, which is shown as the outside loop in Figure 8.20. [Pg.323]

Remark 1 Steps (i) and (ii) are applied to the overall HEN without decomposing it into subnetworks. It is assumed, however, that we have a fixed HRAT for which we calculated the minimum utility cost. The HRAT can be optimized by using the golden section search in the same way that we described it in Figure 8.20. [Pg.325]

Significant new evidence is the self-similarity of sub-atomic, atomic, biological, planetary and galactic structures, all related to the golden section. The astronomical structures are assumed to trace out the shape of local space. The obvious conclusion is that all of space has a uniform non-zero characteristic curvature, conditioned by the universal constants tt and r. Space, in this sense, is to be interpreted as equivalent to the three-dimensional sub-space of the Robertson-Walker metric [104]. In standard cosmology this sub-space... [Pg.288]

Some alchemists even considered gold as condensed sunbeams [1] and used to represent it by the symbol of a circle, the hallmark of mathematical perfection. Let us recall in this respect, e.g., the Golden Section in geometry, the concept of a gold number in colloidal chemistry after R. A. Zsigmondy (Z. Anal. Chem. XL, 697 (1901)) and J. B. Richter and M. Faraday (Phil. Trans. CXLVII, 145 (1857), and the Golden Rule in quantum theory. [Pg.245]

Figure 2. Comparison of theoretical and experimental total cross sections for e-H, scattering. Curves are as follows (1) represents the effective optical potential (2) represents the experiment by Golden and (3) represents the experiment by... Figure 2. Comparison of theoretical and experimental total cross sections for e-H, scattering. Curves are as follows (1) represents the effective optical potential (2) represents the experiment by Golden and (3) represents the experiment by...
Let aj < bj < Cj < dj, where [a, is the interval of uncertainty at iteration k and assume that [<3i, di] = [a, d. Since functional evaluations are the most expensive step in the process, the golden section method reduces the amount of overall work by intelligently choosing symmetric points bj and Cj so that they can be reused on successive iterations, as illustrated in Figure 8. This is achieved by using the relationships b = Xa + (1 - X)d and = (1 - A)% + Xdj where A = 0.618. Observe that b and are simply expressed as convex combinations of % and idj A summary of the golden section algorithm follows ... [Pg.2548]

When the NLP problem consists of only one decision variable (or can be reduced to one), with lower and upper bounds, the optimal solution can be found readily with a spreadsheet, or by one of several structured and efficient search methods, including region elimination, derivative based, and point estimation, as described in detail by Reklaitis et al. (1983). Of the search methods, the golden-section method (involving region elimination) is reasonably efficient, reliable, easily implemented, and widely used. Therefore, it is described and illustrated by example here. [Pg.626]

The determination of the minimum of the objective function by changing the values of Ani can be performed iteratively or with the help of appropriate solvers (e.g., one-dimensional search routines, such as the method of the golden section or the Fibonacci search [11]). [Pg.555]

The mathematical regularity of the proportions of the Crystal Palace helped simplify construction. Paxton determined the basic unit of length for the building not by some aesthetically based golden section, but by the requirements of the exhibition space and a fundamental technological constraint in 1850, sheets of glass longer than about four feet were not only very costly to... [Pg.141]

This so-called golden section or golden ratio is defined by either of the irrational numbers... [Pg.2]

Apart from the relative abundance of isotopes, all other basic data usually shown on a periodic table of the elements are predicted by elementary number theory. Based on the periodic table shown as an Appendix, the chemically important parameters of ionization radius and electronegativity have been used, together with the golden section and golden spirals, to derive all essential parameters pertaining to covalent interaction and the optimization of molecular structure by MM. The detailed results are described in the preceding chapters in this volume. [Pg.174]

The simplest theoretical description of the photon capture cross-section is given by Fermi s Golden Rule... [Pg.268]

In a 500 ml. Pyrex round-bottomed flask, provided with a reflux condenser, place a mixture of 40 g. of freshly-distUled phenylhydrazine (Section IV.89) and 14 g. of urea (previously dried for 3 hours at 100°). Immerse the flask in an oil bath at 155°. After about 10 minutes the urea commences to dissolve accompanied by foaming due to evolution of ammonia the gas evolution slackens after about 1 hour. Remove the flask from the oil bath after 135 minutes, allow it to cool for 3 minutes, and then add 250 ml. of rectified spirit to the hot golden-yellow oil some diphenylcarbazide will crystallise out. Heat under reflux for about 15 minutes to dissolve the diphenylcarbazide, filter through a hot water funnel or a pre-heated Buchner fuimel, and cool the alcoholic solution rapidly in a bath of ice and salt. After 30 minutes, filter the white crystals at the pump, drain well, and wash twice with a little ether. Dry upon filter paper in the air. The yield of diphenylcarbazide, m.p. 171 °, is 34 g. A further 7 g. may be obtained by concentrating the filtrate under reduced pressure. The compound may be recrystallised from alcohol or from glacial acetic acid. [Pg.955]


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