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3.
In this paper, we investigate the evolution of joint invariants under invariant geometric flows using the theory of equivariant moving frames and the induced invariant discrete variational complex. For certain arc length preserving planar curve flows invariant under the special Euclidean group , the special linear group , and the semidirect group , we find that the induced evolution of the discrete curvature satisfies the differential‐difference mKdV, KdV, and Burgers' equations, respectively. These three equations are completely integrable, and we show that a recursion operator can be constructed by precomposing the characteristic operator of the curvature by a certain invariant difference operator. Finally, we derive the constraint for the integrability of the discrete curvature evolution to lift to the evolution of the discrete curve itself. 相似文献
4.
Y. Wardi 《Journal of Optimization Theory and Applications》1989,61(3):473-485
A stochastic algorithm for finding stationary points of real-valued functions defined on a Euclidean space is analyzed. It is based on the Robbins-Monro stochastic approximation procedure. Gradient evaluations are done by means of Monte Carlo simulations. At each iteratex
i
, one sample point is drawn from an underlying probability space, based on which the gradient is approximated. The descent direction is against the approximation of the gradient, and the stepsize is 1/i. It is shown that, under broad conditions, w.p.1 if the sequence of iteratesx
1,x
2,...generated by the algorithm is bounded, then all of its accumulation points are stationary. 相似文献
5.
José E. Valdés 《Operations Research Letters》2006,34(1):49-52
Components C1 and C2 form a series system. Suppose we can allocate the spare R1 in parallel with C1 and the spare R2 in parallel with C2, or otherwise, allocate R1 with C2 and R2 with C1. In this paper, we compare these two options using hazard rate ordering. 相似文献
6.
B. Dubrulle F. Hersant 《The European Physical Journal B - Condensed Matter and Complex Systems》2002,26(3):379-386
We generalize an analogy between rotating and stratified shear flows. This analogy is summarized in Table 1. We use this analogy
in the unstable case (centrifugally unstable flow vs. convection) to compute the torque in Taylor-Couette configuration, as a function of the Reynolds number. At low Reynolds
numbers, when most of the dissipation comes from the mean flow, we predict that the non-dimensional torque G = T/ν2
L, where L is the cylinder length, scales with Reynolds number R and gap width η, G = 1.46η3/2(1 - η)-7/4
R
3/2. At larger Reynolds number, velocity fluctuations become non-negligible in the dissipation. In these regimes, there is no
exact power law dependence the torque versus Reynolds. Instead, we obtain logarithmic corrections to the classical ultra-hard (exponent 2) regimes: G = 0.50
. These predictions are found to be in excellent agreement with avail-able experimental data. Predictions for scaling of velocity
fluctuations are also provided.
Received 7 June 2001 and Received in final form 7 December 2001 相似文献
7.
Fabio Schoen 《Journal of Global Optimization》1991,1(3):207-228
In this paper stochastic algorithms for global optimization are reviewed. After a brief introduction on random-search techniques, a more detailed analysis is carried out on the application of simulated annealing to continuous global optimization. The aim of such an analysis is mainly that of presenting recent papers on the subject, which have received only scarce attention in the most recent published surveys. Finally a very brief presentation of clustering techniques is given. 相似文献
8.
Several a priori tests of a systematic stochastic mode reduction procedure recently devised by the authors [Proc. Natl. Acad. Sci. 96 (1999) 14687; Commun. Pure Appl. Math. 54 (2001) 891] are developed here. In this procedure, reduced stochastic equations for a smaller collections of resolved variables are derived systematically for complex nonlinear systems with many degrees of freedom and a large collection of unresolved variables. While the above approach is mathematically rigorous in the limit when the ratio of correlation times between the resolved and the unresolved variables is arbitrary small, it is shown here on a systematic hierarchy of models that this ratio can be surprisingly big. Typically, the systematic reduced stochastic modeling yields quantitatively realistic dynamics for ratios as large as 1/2. The examples studied here vary from instructive stochastic triad models to prototype complex systems with many degrees of freedom utilizing the truncated Burgers–Hopf equations as a nonlinear heat bath. Systematic quantitative tests for the stochastic modeling procedure are developed here which involve the stationary distribution and the two-time correlations for the second and fourth moments including the resolved variables and the energy in the resolved variables. In an important illustrative example presented here, the nonlinear original system involves 102 degrees of freedom and the reduced stochastic model predicted by the theory for two resolved variables involves both nonlinear interaction and multiplicative noises. Even for large value of the correlation time ratio of the order of 1/2, the reduced stochastic model with two degrees of freedom captures the essentially nonlinear and non-Gaussian statistics of the original nonlinear systems with 102 modes extremely well. Furthermore, it is shown here that the standard regression fitting of the second-order correlations alone fails to reproduce the nonlinear stochastic dynamics in this example. 相似文献
9.
Optimization technologies and environmental applications 总被引:1,自引:0,他引:1
10.
Dalila B. M. M. Fontes Eleni Hadjiconstantinou Nicos Christofides 《Journal of Global Optimization》2006,34(1):97-125
In this paper we obtain Lower Bounds (LBs) to concave cost network flow problems. The LBs are derived from state space relaxations
of a dynamic programming formulation, which involve the use of non-injective mapping functions guaranteing a reduction on
the cardinality of the state space. The general state space relaxation procedure is extended to address problems involving
transitions that go across several stages, as is the case of network flow problems. Applications for these LBs include: estimation
of the quality of heuristic solutions; local search methods that use information of the LB solution structure to find initial
solutions to restart the search (Fontes et al., 2003, Networks, 41, 221–228); and branch-and-bound (BB) methods having as
a bounding procedure a modified version of the LB algorithm developed here, (see Fontes et al., 2005a). These LBs are iteratively
improved by penalizing, in a Lagrangian fashion, customers not exactly satisfied or by performing state space modifications.
Both the penalties and the state space are updated by using the subgradient method. Additional constraints are developed to
improve further the LBs by reducing the searchable space. The computational results provided show that very good bounds can
be obtained for concave cost network flow problems, particularly for fixed-charge problems. 相似文献