Genetic algorithms for approximate similarity queries

Renato Bueno; Agma J.M. Traina; Caetano Traina

doi:10.1016/j.datak.2006.08.013

Genetic algorithms for approximate similarity queries

Data & Knowledge Engineering ◽

10.1016/j.datak.2006.08.013 ◽

2007 ◽

Vol 62 (3) ◽

pp. 459-482 ◽

Cited By ~ 12

Author(s):

Renato Bueno ◽

Agma J.M. Traina ◽

Caetano Traina

Keyword(s):

Genetic Algorithms ◽

Similarity Queries ◽

Approximate Similarity

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Accelerating approximate similarity queries using genetic algorithms

Proceedings of the 2005 ACM symposium on Applied computing - SAC '05 ◽

10.1145/1066677.1066820 ◽

2005 ◽

Cited By ~ 1

Author(s):

Renato Bueno ◽

Agma J. M. Traina ◽

Caetano Traina

Keyword(s):

Genetic Algorithms ◽

Similarity Queries ◽

Approximate Similarity

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Using the distance distribution for approximate similarity queries in high-dimensional metric spaces

Proceedings. Tenth International Workshop on Database and Expert Systems Applications. DEXA 99 ◽

10.1109/dexa.1999.795166 ◽

1999 ◽

Cited By ~ 4

Author(s):

P. Ciaccia ◽

M. Patella

Keyword(s):

Metric Spaces ◽

Distance Distribution ◽

High Dimensional ◽

Similarity Queries ◽

Approximate Similarity

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Hierarchical time-optimal control of a continuous copolymerization reactor during start-up or grade change operation using genetic algorithms

Computers & Chemical Engineering ◽

10.1016/s0098-1354(97)00186-5 ◽

1997 ◽

Vol 21 (1-2) ◽

pp. S1037-S1042

Author(s):

H Moo

Keyword(s):

Optimal Control ◽

Genetic Algorithms ◽

Time Optimal Control ◽

Grade Change ◽

Start Up ◽

Time Optimal ◽

Change Operation ◽

Grade Change Operation

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Genetic Algorithms—a Tool for OR?

Journal of the Operational Research Society ◽

10.1057/palgrave.jors.0470406 ◽

1996 ◽

Vol 47 (4) ◽

pp. 550-561 ◽

Cited By ~ 2

Author(s):

Kathryn A Dowsland

Keyword(s):

Genetic Algorithms

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Road Horizontal Alignment Design Method for Continuous Loop Area in Autonomous Vehicles Proving Ground Based on Genetic Algorithms

CICTP 2020 ◽

10.1061/9780784483053.163 ◽

2020 ◽

Author(s):

Junyi Chen ◽

Rubing Li ◽

Xingyu Xing ◽

Lu Xiong

Keyword(s):

Genetic Algorithms ◽

Autonomous Vehicles ◽

Design Method ◽

Horizontal Alignment ◽

Loop Area

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

Al-Kitab Journal for Pure Sciences ◽

10.32441/kjps.v1i1.87 ◽

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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