Application of Interactive Genetic Algorithm in Fractal Art Pattern Design System

Jiang, Ling; Zhou, Weiliang

doi:10.1109/nmitcon58196.2023.10276254

Cited by 1 publication

(1 citation statement)

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“…The main idea behind Genetic Algorithm Based on Operator Optimization is to develop and optimize genetic operators like crossover and mutation to better meet the needs of illustration art design [7]. These operators play an important role in the evolution of solutions within a genetic algorithm by emulating the mechanisms of genetic recombination and mutation found in natural evolution [8]. By optimizing these operators, it is feasible to direct the search process toward creating artwork that fits specified aesthetic requirements while simultaneously encouraging diversity and the investigation of creative solutions [9].…”

Section: Introductionmentioning

confidence: 99%

Genetic Algorithm Based on Operator Optimization in Illustration Art Design

Shaoqiang Chen

2024

jes

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The current research explores the use of Genetic Algorithm (GA) Based on Operator Optimization in graphic art design, to improve the creative process using computational methods. By improving genetic operators such as crossover and mutation, the technique streamlines the creation of visually appealing artwork, allowing artists to efficiently express their distinctive vision. Through testing and research, the study reveals the effectiveness of this strategy in automating repetitive processes, exploring new creative pathways, and creating audience-resonant artwork. The combination of computational intelligence and creative intuition improves efficiency while also encouraging creativity and experimentation in the realm of graphic art design. The work sheds light on the revolutionary potential of Genetic algorithms (GA) based on Operator Optimization, highlighting areas for future research and development at the interface of technology and artistic effort. The results indicate that a better genetic algorithm (GA) provides efficacy and optimizes the operator in art design using a genetic algorithm.

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Section: Introductionmentioning

confidence: 99%

Genetic Algorithm Based on Operator Optimization in Illustration Art Design

Shaoqiang Chen

2024

jes

View full text Add to dashboard Cite

show abstract

Application of Interactive Genetic Algorithm in Fractal Art Pattern Design System

Cited by 1 publication

References 15 publications

Genetic Algorithm Based on Operator Optimization in Illustration Art Design

Genetic Algorithm Based on Operator Optimization in Illustration Art Design

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