Corrigendum to: Optimum profile modifications of spur gears by means of genetic algorithms

2012 ◽  
Vol 331 (21) ◽  
pp. 4825-4829 ◽  
Author(s):  
Marco Barbieri ◽  
Giorgio Bonori ◽  
Francesco Pellicano
Keyword(s):  
Genetic Algorithms ◽  
Spur Gears ◽  
Optimum Profile

Optimum profile modifications of spur gears by means of genetic algorithms

2008 ◽  
Vol 313 (3-5) ◽  
pp. 603-616 ◽  
Author(s):  
Giorgio Bonori ◽  
Marco Barbieri ◽  
Francesco Pellicano
Keyword(s):  
Genetic Algorithms ◽  
Spur Gears ◽  
Optimum Profile

Optimum Profile Modifications for the Minimization of Static Transmission Errors of Spur Gears

1986 ◽  
Vol 108 (1) ◽  
pp. 86-94 ◽  
Author(s):  
M. S. Tavakoli ◽  
D. R. Houser
Keyword(s):  
Transmission Error ◽  
Spur Gears ◽  
Contact Ratio ◽  
Transmission Errors ◽  
Gear Mesh ◽  
Starting Point ◽  
Frequency Components ◽  
Design Loads ◽  
Static Transmission Error ◽  
Optimum Profile

A procedure for computing static transmission errors and tooth load sharing was developed for low and high contact ratio internal and external spur gears. A suitable optimization algorithm was used to minimize any combination of the harmonics of gear mesh frequency components of the static transmission error. Different combinations of tip and root relief may be used to achieve optimization. These include varying the starting point of relief and varying the magnitude of relief, and selecting the gear and/or the pinion teeth to be tip and/or root-relieved. Also, there exists an option for using either linear or parabolic relief. In addition to the presentation of optimal profile modifications, the effects of off-design loads, nonoptimum modifications, and random spacing errors are presented.

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).

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