aThe method can be directly applied to the design of periodic structures, but the computational cost is expensive because it has to perform two finite-element analyses in each iteration, one for the macroscale optimization problem and the other for the microscale sub-optimization problem. 方法可以直...
Harnessing the Cloud for Securely Solving Large-Scale Systems of Linear Equations Cloud computing economically enables customers with limited computational resources to outsource large-scale computations to the cloud. However, how to pro... W Cong,K Ren,W Jia,... - International Conference on ...
Li et al.[75] proposed a surrogate-assisted multi-level evaluation method to reduce the expensive computational cost in op- timizing the CNN hyperparameters. In this method, two levels of evaluation, i.e., surrogate-based and training- based FE, are cooperated to balance the optimization ac...
There is a subscription-based model available for small or independent developers. It costs $9.90 a month and gives access to all the latest features. Why are some software tools so expensive? There are many factors contributing to the higher cost of complex software tools: Sophisticated software...
We study the model-checking problem for WMTL, a cost-extension of the linear-time timed temporal logic MTL, that is interpreted over weighted timed automata. We draw a complete picture of the decidability for that problem: it is decidable only for the cl
Computationally expensive constrained optimization problems are challenging owing to their high complexity and computational cost. To solve these problems efficiently, a kriging-assisted bi-objective constrained global optimization (BOCGO) algorithm is developed, where three phases with three bi-objective ...
Zonal or multi-compartmental modeling12,13 has been used in some areas such as CFD simulations to overcome the computational cost of transient simulations, however the inherent problem with this approach is the difficulty in defining the zones or compartment that efficiently capture the flow behavior...
The proposed surrogate-assisted EA (SAEA) uses Kriging to approximate each objective function to reduce the computational cost. In managing the Kriging models, the algorithm focuses on the balance of diversity and convergence by making use of the uncertainty information in the approximated objective ...
Many disciplines involve computationally expensive multiobjective optimisation problems. Surrogate-based methods are commonly used in the literature to alleviate the computational cost. In this paper, we develop an interactive surrogate-based method called SURROGATE-ASF to solve computationally expensive multi...
For multi-objective design of multi-parameter antenna structures, optimization efficiency and computational cost are two major concerns. In this paper, an improved multi-objective evolutionary algorithm based on decomposition (MOEA/D) is... J Dong,Q Li,L Deng - AEU - International Journal of Elec...