Genetic algorithms and the search for optimal database index selection

1991 ◽  
pp. 249-255 ◽  
Author(s):  
Farshad Fotouhi ◽  
Carlos E. Galarce
Keyword(s):  
Genetic Algorithms ◽  
Index Selection ◽  
Database Index

scholarly journals GADIS: A Genetic Algorithm for Database Index Selection (S)

2019 ◽  
Author(s):  
Priscilla Neuhaus ◽  
Julia Couto ◽  
Jonatas Wehrmann ◽  
Duncan Ruiz ◽  
Felipe Meneguzzi
Keyword(s):  
Genetic Algorithm ◽  
Index Selection ◽  
Database Index

scholarly journals A mapreduce relational-database index-selection tool

2021 ◽  
Author(s):  
Fatimah Alsayoud
Keyword(s):  
Relational Database ◽  
Index Selection ◽  
Selection Tool ◽  
Database Index

A mapreduce relational-database index-selection tool

scholarly journals A mapreduce relational-database index-selection tool

2021 ◽  
Author(s):  
Fatimah Alsayoud
Keyword(s):  
Relational Database ◽  
Index Selection ◽  
Selection Tool ◽  
Database Index

A mapreduce relational-database index-selection tool

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
Sign in / Sign up

Export Citation Format

Share Document