scholarly journals Generative Art Images by Complex Functions Based Genetic Algorithm

2008 ◽  
pp. 125-134 ◽  
Author(s):  
Hong Liu ◽  
Xiyu Liu
Keyword(s):  
Genetic Algorithm ◽  
Generative Art ◽  
Complex Functions

Researches on Function Optimization Problems Based on Chaotic Immune Genetic Algorithms

2012 ◽  
Vol 616-618 ◽  
pp. 2064-2067
Author(s):  
Yong Gang Che ◽  
Chun Yu Xiao ◽  
Chao Hai Kang ◽  
Ying Ying Li ◽  
Li Ying Gong
Keyword(s):  
Genetic Algorithm ◽  
Genetic Algorithms ◽  
Optimization Problems ◽  
Chaotic Map ◽  
Solution Space ◽  
Population Diversity ◽  
Function Optimization ◽  
Initial Population ◽  
Immune Genetic Algorithm ◽  
Complex Functions

To solve the primary problems in genetic algorithms, such as slow convergence speed, poor local searching capability and easy prematurity, the immune mechanism is introduced into the genetic algorithm, and thus population diversity is maintained better, and the phenomena of premature convergence and oscillation are reduced. In order to compensate the defects of immune genetic algorithm, the Hénon chaotic map, which is introduced on the above basis, makes the generated initial population uniformly distributed in the solution space, eventually, the defect of data redundancy is reduced and the quality of evolution is improved. The proposed chaotic immune genetic algorithm is used to optimize the complex functions, and there is an analysis compared with the genetic algorithm and the immune genetic algorithm, the feasibility and effectiveness of the proposed algorithm are proved from the perspective of simulation experiments.

scholarly journals Generative 3D images in a visual evolutionary computing system

2010 ◽  
Vol 7 (1) ◽  
pp. 111-126 ◽  
Author(s):  
Hong Liu
Keyword(s):  
Genetic Algorithm ◽  
Binary Tree ◽  
Computer Aided Design ◽  
Complex Function ◽  
Computing System ◽  
Design System ◽  
3D Images ◽  
Design Evolution ◽  
Complex Functions ◽  
Aided Design

This paper presents a novel computer-aided design system which uses a computational approach to producing 3D images for stimulating creativity of designers. It introduces the genetic algorithm first. Then a binary tree based genetic algorithm is presented. This approach is illustrated by a 3D image generative example, which uses complex function expressions as chromosomes to form a binary tree, and all genetic operations are performed on the binary tree. Corresponding complex functions are processed by MATLAB software to form 3D images of artistic flowers. This generative design is integrated with a visualization interface, which allows designers to interact and select from instances for design evolution. It shows the system is able to enhance the possibility of discovering various potential design solutions.

QUANTUMIZED GENETIC ALGORITHM FOR SEGMENTATION AND OPTIMIZATION TASKS

2020 ◽  
Vol 32 (03) ◽  
pp. 2050022
Author(s):  
Malihe Sabeti ◽  
Laleh Karimi ◽  
Naemeh Honarvar ◽  
Mahsa Taghavi ◽  
Reza Boostani
Keyword(s):  
Genetic Algorithm ◽  
Search Algorithm ◽  
Skeletal Maturity ◽  
Harmony Search ◽  
Harmony Search Algorithm ◽  
The Other ◽  
Left Hand ◽  
Optimization Task ◽  
Complex Functions ◽  
Representation Scheme

Specialists mostly assess the skeletal maturity of short-height children by observing their left hand X-Ray image (radiograph), whereas precise separation of areas capturing the bones and growing plates is always not possible by visual inspection. Although a few attempts are made to estimate a suitable threshold for segmenting digitized radiograph images, their results are not still promising. To finely estimate segmentation thresholds, this paper presents the quantumized genetic algorithm (QGA) that is the integration of quantum representation scheme in the basic genetic algorithm (GA). This hybridization between quantum inspired computing and GA has led to an efficient hybrid framework that achieves better balance between the exploration and the exploitation capabilities. To assess the performance of the proposed quantitative bone maturity assessment framework, we have collected an exclusive dataset including 65 left-hand digitized images, aged from 3 to 13 years. Thresholds are estimated by the proposed method and the results are compared to harmony search algorithm (HSA), particle swarm optimization (PSO), quantumized PSO and standard GA. In addition, for more comparison of the proposed method and the other mentioned evolutionary algorithms, ten known benchmarks of complex functions are considered for optimization task. Our results in both segmentation and optimization tasks show that QGA and GA provide the best optimization results in comparison with the other mentioned algorithms. Moreover, the empirical results demonstrate that QGA is able to provide better diversity than that of GA.

The ground state energy of the ±J spin glass from the genetic algorithm

1994 ◽  
Vol 4 (9) ◽  
pp. 1281-1285 ◽  
Author(s):  
P. Sutton ◽  
D. L. Hunter ◽  
N. Jan
Keyword(s):  
Genetic Algorithm ◽  
Spin Glass ◽  
Ground State Energy ◽  
Ground State ◽  
State Energy

A Monoclonal Antibody to the Human Platelet Glycoprotein II b/III a Complex Induces Platelet Activation

1988 ◽  
Vol 60 (01) ◽  
pp. 068-074 ◽  
Author(s):  
Piet W Modderman ◽  
Han G Huisman ◽  
Jan A van Mourik ◽  
Albert E G Kr von dem Borne
Keyword(s):  
Human Platelet ◽  
Adenosine Diphosphate ◽  
Dense Granule ◽  
Platelet Glycoprotein ◽  
Activated Platelets ◽  
Complex Functions ◽  
Slow Aggregation ◽  
Irreversible Aggregation ◽  
Platelet Release ◽  
Aggregation Of Platelets

SummaryThe platelet glycoprotein (GP) IIb/IIIa complex functions as the receptor for fibrinogen on activated platelets. The effects of two anti-GPIIb/IIIa monoclonal antibodies on platelet function were studied. These antibodies, 6C9 and C17, recognized different epitopes, which were exclusively present on the undissociated GPIIb/IIIa complex. Whereas C17 inhibited the binding of fibrinogen to platelets and platelet aggregation induced by adenosine diphosphate (ADP) or collagen, 6C9 caused irreversible aggregation of platelets, both in the presence and absence of extracellular fibrinogen. When incubated with unstirred (nonaggregating) platelets, 6C9 induced release of alpha and dense granule-constituents as well as binding of 125I-fibrinogen to platelets. The latter was evidently mediated in part by platelet-derived ADP, since it was inhibited to a large extent by apyrase, the ADP-hydrolyzing enzyme. F(ab’)2 fragments of 6C9 did not induce platelet-release reactions but caused (slow) aggregation of platelets in the presence of extracellular fibrinogen.These results indicate that binding of an antibody to a specific site on the platelet GPIIb/IIIa complex may cause fibrinogen-mediated aggregation. The Fc part of the platelet-bound antibody appears to be involved in the induction of platelet release.

A Comparative Study of Ant and Genetic Algorithms in Digital Mammography

2018 ◽  
pp. 194-200
Author(s):  
J. Magelin Mary ◽  
Chitra K. ◽  
Y. Arockia Suganthi
Keyword(s):  
Genetic Algorithm ◽  
Image Processing ◽  
Medical Image ◽  
Medical Image Processing ◽  
Processing Technique ◽  
Input Image ◽  
Image Processing Technique ◽  
Computational Time ◽  
Image Mining ◽  
The Individual

Image processing technique in general, involves the application of signal processing on the input image for isolating the individual color plane of an image. It plays an important role in the image analysis and computer version. This paper compares the efficiency of two approaches in the area of finding breast cancer in medical image processing. The fundamental target is to apply an image mining in the area of medical image handling utilizing grouping guideline created by genetic algorithm. The parameter using extracted border, the border pixels are considered as population strings to genetic algorithm and Ant Colony Optimization, to find out the optimum value from the border pixels. We likewise look at cost of ACO and GA also, endeavors to discover which one gives the better solution to identify an affected area in medical image based on computational time.

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