Titlebook: Differential Evolution; A Practical Approach Kenneth V. Price,Rainer M. Storn,Jouni A. Lampinen Textbook 2005 Springer-Verlag Berlin Heidel

BIBLE

植物茂盛

植物群

ineluctable

Yanyan Zhang,Hongjun Li,Ailin Chengo the magnetically nonlinear properties of the iron core. Therefore, the objective function of each individual parameter set in the population of the optimization algorithm is evaluated by the finite element method.

貪心

Non-Imaging Optical Design Using Differential Evolution validates it for two geometric classes of problems. In these the target distribution comes from either a parabolic mirror shape or an elliptical mirror shape. The methodology is also validated for an extended light source.

ODIUM

Optimization of Radial Active Magnetic Bearings by Using Differential Evolution and the Finite Elemeo the magnetically nonlinear properties of the iron core. Therefore, the objective function of each individual parameter set in the population of the optimization algorithm is evaluated by the finite element method.

Neuropeptides

Minimal Representation Multi-Sensor Fusion Using Differential Evolutiondel search problem. The minimal representation approach is based on an information measure as a . for fusion, and provides a framework for integrating information from a variety of sources. The minimal representation size criterion favors the selection of the simplest explanation that is the most li

放棄

不能平靜

Parallel Differential Evolution: Application to 3-D Medical Image Registrationon. The performances of the parallel version are assessed on a 3-D medical image registration problem. Besides yielding accurate registrations, parallel differential evolution exhibits fast convergence and a speedup almost growing linearly with respect to the number of processors.

漫步

Active Compensation in RF-Driven Plasmas by Means of Differential Evolutionefore, 14 mutually interacting parameters (seven phases and seven amplitudes) had to be tuned on-line. In this work, two stochastic optimization algorithms were used for automated tuning of the probe — simulated annealing (SA) and differential evolution (DE). SA was previously used for this problem,