scholarly journals What are grain boundary structures in graphene?

Nanoscale ◽  
2014 ◽  
Vol 6 (8) ◽  
pp. 4309-4315 ◽  
Author(s):  
Zheng-Lu Li ◽  
Zhi-Ming Li ◽  
Hai-Yuan Cao ◽  
Ji-Hui Yang ◽  
Qiang Shu ◽  
...  
Keyword(s):  
Global Optimization ◽  
Grain Boundary ◽  
Differential Evolution ◽  
Differential Evolution Algorithm ◽  
Optimization Method ◽  
Interface Structure ◽  
Global Optimization Method ◽  
Evolution Algorithm

We have developed a new global optimization method for the determination of the interface structure based on the differential evolution algorithm.

scholarly journals Cloud Particles Differential Evolution Algorithm: A Novel Optimization Method for Global Numerical Optimization

2015 ◽  
Vol 2015 ◽  
pp. 1-36 ◽  
Author(s):  
Wei Li ◽  
Lei Wang ◽  
Quanzhu Yao ◽  
Qiaoyong Jiang ◽  
Lei Yu ◽  
...  
Keyword(s):  
Solid State ◽  
Differential Evolution ◽  
Liquid State ◽  
Differential Evolution Algorithm ◽  
Optimization Method ◽  
Benchmark Problems ◽  
Gaseous State ◽  
Mutation Strategy ◽  
Evolution Algorithm ◽  
Cloud Particles

We propose a new optimization algorithm inspired by the formation and change of the cloud in nature, referred to as Cloud Particles Differential Evolution (CPDE) algorithm. The cloud is assumed to have three states in the proposed algorithm. Gaseous state represents the global exploration. Liquid state represents the intermediate process from the global exploration to the local exploitation. Solid state represents the local exploitation. The best solution found so far acts as a nucleus. In gaseous state, the nucleus leads the population to explore by condensation operation. In liquid state, cloud particles carry out macrolocal exploitation by liquefaction operation. A new mutation strategy called cloud differential mutation is introduced in order to solve a problem that the misleading effect of a nucleus may cause the premature convergence. In solid state, cloud particles carry out microlocal exploitation by solidification operation. The effectiveness of the algorithm is validated upon different benchmark problems. The results have been compared with eight well-known optimization algorithms. The statistical analysis on performance evaluation of the different algorithms on 10 benchmark functions and CEC2013 problems indicates that CPDE attains good performance.

scholarly journals Location Optimization for Square Array Antennas Using Differential Evolution Algorithm

2016 ◽  
Vol 2016 ◽  
pp. 1-7 ◽  
Author(s):  
Erkan Afacan
Keyword(s):  
Differential Evolution ◽  
Antenna Arrays ◽  
Differential Evolution Algorithm ◽  
Difference Sets ◽  
Location Optimization ◽  
Array Antennas ◽  
Evolution Algorithm ◽  
Thinned Array ◽  
Square Array

In recent works thinned arrays giving minimum peak sidelobe levels for planar square antenna arrays are obtained using Hadamard difference sets. In the current work thinned array configurations giving lower peak sidelobe levels than those given in the literature are obtained for square arrays of6×6,8×8,12×12, and16×16elements. Differential evolution algorithm is used in the determination of the antenna locations.

Research of Differential Evolution Algorithm for Motor Control

2014 ◽  
Vol 596 ◽  
pp. 216-221
Author(s):  
Zong Fu Wu
Keyword(s):  
Global Optimization ◽  
Differential Evolution ◽  
High Efficiency ◽  
Differential Evolution Algorithm ◽  
Optimization Analysis ◽  
Searching Strategy ◽  
Evolution Algorithm ◽  
Searching Ability ◽  
Improved Differential Evolution Algorithm ◽  
Chaos Searching

An improved differential evolution algorithm for solving nonlinear equations of electrical motor system is explored. The algorithm is to convert equations into an optimization problem and, by keeping consideration of the evolution process and adopting dynamic parameters adjusting mechanism, the algorithm can improve searching efficiency and implement real-time surveillance for population overlapping. The Chaos searching strategy is used for overlapping individual to further improve the ability of global optimization. Analysis results of induction motor motion parameters show that the improved differential evolution algorithm proposed in this paper has high efficiency and powerful global optimization searching ability.

Sign in / Sign up

Export Citation Format

Share Document