We discuss the rate of convergence with respect to the number of ants: we give experimental and theoretical arguments that suggest that this convergence rate can be superlinear with respect to the number of agents. Furthermore, we explain how this model can be extended in order to solve ...
Under the background of the optimization of the maintenance plan of the traditional generator set, this chapter establishes theoptimizing modelof the new maintenance plan with economic and technological considerations. To solve the disadvantages of low convergence speed of ant colony algorithm and easy ...
Extensive numerical experiments show that the algorithm can reliably solve a wide range of problems at a speed at least several times faster than many nuclear-norm minimization algorithms. In addition, convergence of this nonlinear SOR algorithm to a stationary point is analyzed. 展开 ...
To further improve the convergence speed, we trained our model on a small subsample, \(n = 100\), and implemented these parameter estimates as start values of \(\varvec{\theta }\) in the model using the original sample. 4.1 Selection of the Number of Segments As the number of segments...
Therefore, based on the first layer, we add 1 × 3 and 1 × 5 convolution kernels to increase the receptive field of the network and ensure that long-distance features are not omitted. In addition, to avoid gradient disappearance and accelerate convergence of the network, we add ...
To solve this problem, many methods have been proposed to mitigate the artifacts of inverse Radon transform or back projection. For example, the weighted back projection (WBP) method corrects back projection by applying a ramp filter that dumps the low-frequency information and enhances the high-...
The Q-Superlinear Convergence of a Collinear Scaling Algorithm for Unconstrained Optimization In [4], we present a trust region method of conic model for unconstrained optimization problems. As a continuing work, in this paper, we describe a ... DC Sorensen - 《Siam Journal on Numerical ...
81 To conclude, in this class of horizontal innovation models, international migration of skilled labor leads to divergence rather than convergence of per-capita income across economies. Directed technical change As emphasized in Acemoglu (1998, 2002), an increase in the size of the high-skilled ...
Time-consuming training due to weak inductive bias: DRL require a long time for training until convergence; as reported by Botvinick et al. (2019), this is caused by weak inductive bias (discussed in Chapter 1, Section 1.2) and, Although weak inductive bias enables DRL to handle large varia...
Nash equilibria networks can contain some mutually beneficial link(s) that are left aside. To solve this coordination problem when employing Nash equilibria, the notion of pairwise Nash stabilitydwas introduced. Pairwise Nash stable (PNSt) networks are at the intersection of the set of Nash equil...