Pixel classification using variable string genetic algorithms with chromosome differentiation

S. Bandyopadhyay; S.K. Pal

doi:10.1109/36.905238

Pixel classification using variable string genetic algorithms with chromosome differentiation

IEEE Transactions on Geoscience and Remote Sensing ◽

10.1109/36.905238 ◽

2001 ◽

Vol 39 (2) ◽

pp. 303-308 ◽

Cited By ~ 70

Author(s):

S. Bandyopadhyay ◽

S.K. Pal

Keyword(s):

Genetic Algorithms ◽

Pixel Classification ◽

Chromosome Differentiation

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Prostate Segmentation Using Pixel Classification and Genetic Algorithms

Lecture Notes in Computer Science - MICAI 2005: Advances in Artificial Intelligence ◽

10.1007/11579427_93 ◽

2005 ◽

pp. 910-917 ◽

Cited By ~ 1

Author(s):

Fernando Arámbula Cosío

Keyword(s):

Genetic Algorithms ◽

Pixel Classification ◽

Prostate Segmentation

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Genetic Algorithms with Chromosome Differentiation (GACD) Based Approach for Process Plan Selection Problems

Evolutionary Computing in Advanced Manufacturing ◽

10.1002/9781118161883.ch5 ◽

2011 ◽

pp. 77-94

Author(s):

Nishikant Mishra ◽

Vikas Kumar

Keyword(s):

Genetic Algorithms ◽

Process Plan ◽

Chromosome Differentiation ◽

Selection Problems ◽

Plan Selection ◽

Process Plan Selection

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Incorporating chromosome differentiation in genetic algorithms

Information Sciences ◽

10.1016/s0020-0255(97)00069-8 ◽

1998 ◽

Vol 104 (3-4) ◽

pp. 293-319 ◽

Cited By ~ 18

Author(s):

S. Bandyopadhyay ◽

S.K. Pal ◽

U. Maulik

Keyword(s):

Genetic Algorithms ◽

Chromosome Differentiation

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Pattern classification with genetic algorithms: Incorporation of chromosome differentiation

Pattern Recognition Letters ◽

10.1016/s0167-8655(97)00005-6 ◽

1997 ◽

Vol 18 (2) ◽

pp. 119-131 ◽

Cited By ~ 12

Author(s):

Sanghamitra Bandyopadhyay ◽

Sankar K. Pal

Keyword(s):

Genetic Algorithms ◽

Pattern Classification ◽

Chromosome Differentiation

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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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