GADPO: Genetic Algorithm based on Dominance for Primer Optimization

Rodríguez-Bejarano, Fernando M.; Vega-Rodríguez, Miguel A.; Santander-Jiménez, Sergio

doi:10.1016/j.eswa.2023.122206

Cited by 3 publications

(1 citation statement)

References 30 publications

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“…Colour selection, composition, texture, and style are among the many difficult and subjective considerations made during the illustration creation process. Historically, artists have relied on intuition, expertise, and manual effort to create artwork [4]. However, with the introduction of computational approaches, there is a growing interest in using algorithms to automate and enhance the creative process.…”

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

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A temperature compensated fiber probe for highly sensitive detection in virus gene biosensing

Han,

Zhang,

Zhang

et al. 2024

Analytica Chimica Acta

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Optimizing Terminal Water Management in Irrigation District Using Water Balance and Genetic Algorithm

Zhao,

Chen,

Chen

et al. 2024

Agronomy

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Water delivery management in China’s irrigation districts has traditionally prioritized the main canal system, often overlooking the water-saving potential of the final canals and field irrigation, which offer substantial opportunities to enhance water use efficiency and conserve agricultural water resources. This study summarizes and defines the integrated water management of final canals and field irrigation as terminal water management. An optimization method was developed to improve terminal water management, which includes optimizing irrigation quotas based on water balance and scheduling final canal water delivery to minimize seepage losses. A genetic algorithm was employed to solve the problem. The method was applied to the Hongjin irrigation district in Jiangsu Province, China. In 2020, paddy water management was observed, revealing that the irrigation amount for organic and traditional rice was 1113 mm and 956 mm, respectively. Conventional irrigation and water delivery practices have led to extensive drainage, significant rainwater wastage, and inefficient water use. The optimized irrigation quotas for organic and traditional rice resulted in water savings of 302.5 mm and 325.9 mm, respectively, compared to the 2020 monitored data. An irrigation event in early August during a 75% hydrological frequency year was selected as an example. With conventional scheduling, optimized final canal water delivery scheduling reduced the seepage losses from 6.3% to 4.6%, shortened the irrigation time from 17 h to 14 h, and stabilized canal flow rates. The proposed optimization method is a valuable tool for enhancing terminal water management and supporting better irrigation decisions in irrigation districts.

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GADPO: Genetic Algorithm based on Dominance for Primer Optimization

Cited by 3 publications

References 30 publications

Genetic Algorithm Based on Operator Optimization in Illustration Art Design

Genetic Algorithm Based on Operator Optimization in Illustration Art Design

A temperature compensated fiber probe for highly sensitive detection in virus gene biosensing

Optimizing Terminal Water Management in Irrigation District Using Water Balance and Genetic Algorithm

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