Genetic Algorithms for the Design of Composite Panels

1995 ◽  
pp. 129-143 ◽  
Author(s):  
S. Nagendra ◽  
R. T. Haftka ◽  
Z. Gürdal
Keyword(s):  
Genetic Algorithms ◽  
Composite Panels

Genetic Algorithms for the Design of Composite Panels

1996 ◽  
pp. 10-29 ◽  
Author(s):  
R. T. Haftka ◽  
R. Le Riche ◽  
P. Harrison
Keyword(s):  
Genetic Algorithms ◽  
Composite Panels

Detection and sizing of delamination cracks in composite panels using speckle interferometry and genetic algorithms

2003 ◽  
Author(s):  
Jonathan M. Huntley ◽  
Charles R. Coggrave ◽  
Alejandro Maranon ◽  
Andrew D. Nurse ◽  
Luis A. Rivera ◽  
...  
Keyword(s):  
Genetic Algorithms ◽  
Speckle Interferometry ◽  
Composite Panels ◽  
Delamination Cracks

scholarly journals Optimization of composite panels using neural networks and genetic algorithms

2003 ◽  
pp. 2359-2363 ◽  
Author(s):  
W. Ruijter ◽  
R. Spallino ◽  
L. Warnet ◽  
A. de Boer
Keyword(s):  
Neural Networks ◽  
Genetic Algorithms ◽  
Composite Panels

Genetic Algorithms—a Tool for OR?

1996 ◽  
Vol 47 (4) ◽  
pp. 550-561 ◽  
Author(s):  
Kathryn A Dowsland
Keyword(s):  
Genetic Algorithms

Enhanced Artificial Intelligent Method for Representing the Photonic Crystal Fiber Profile Index

2018 ◽  
Vol 1 (1) ◽  
pp. 2-19
Author(s):  
Mahmood Sh. Majeed ◽  
Raid W. Daoud
Keyword(s):  
Genetic Algorithms ◽  
Photonic Crystal ◽  
Photonic Crystal Fiber ◽  
New Method ◽  
Proper Solution ◽  
Artificial Intelligent ◽  
Crystal Fiber ◽  
Fitness Value ◽  
First Pass ◽  
Crossover And Mutation

A new method proposed in this paper to compute the fitness in Genetic Algorithms (GAs). In this new method the number of regions, which assigned for the population, divides the time. The fitness computation here differ from the previous methods, by compute it for each portion of the population as first pass, then the second pass begin to compute the fitness for population that lye in the portion which have bigger fitness value. The crossover and mutation and other GAs operator will do its work only for biggest fitness portion of the population. In this method, we can get a suitable and accurate group of proper solution for indexed profile of the photonic crystal fiber (PCF).

Optimizing Time-multiplexing Raster Cellular Neural Network simulator using genetic algorithms with RK8(6)

2011 ◽  
Vol 3 (6) ◽  
pp. 87-90
Author(s):  
O. H. Abdelwahed O. H. Abdelwahed ◽  
◽  
M. El-Sayed Wahed ◽  
O. Mohamed Eldaken
Keyword(s):  
Neural Network ◽  
Genetic Algorithms ◽  
Cellular Neural Network ◽  
Network Simulator

Optimization of Linear Equations using Genetic Algorithms

2011 ◽  
Vol 2 (3) ◽  
pp. 56-58
Author(s):  
Roshni .V Patel ◽  
◽  
Jignesh. S Patel
Keyword(s):  
Genetic Algorithms ◽  
Linear Equations
Sign in / Sign up

Export Citation Format

Share Document