• KSII Transactions on Internet and Information Systems (TIIS)
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• 제2권4호
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• pp.184-193
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• 2008

We examine the performance of genetic algorithms using binary encoding, with respect to a change of basis. Changing the basis can result in a change in the linkage structure inherent in the fitness function. We test three simple functions with differing linkage strengths and analyze the results. Based on an empirical analysis, we show that a better basis results in a smoother fitness landscape, hence genetic algorithms based on the new encoding method provide better performance.

• Journal of Information Processing Systems
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• 제20권2호
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• pp.263-272
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• 2024

A model based on genetic algorithm optimization, GA-SVM, is proposed to warn university students of their status. This model improves the predictive effect of support vector machines. The genetic optimization algorithm is used to train the hyperparameters and adjust the kernel parameters, kernel penalty factor C, and gamma to optimize the support vector machine model, which can rapidly achieve convergence to obtain the optimal solution. The experimental model was trained on open-source datasets and validated through comparisons with random forest, backpropagation neural network, and GA-SVM models. The test results show that the genetic algorithm-optimized radial basis kernel support vector machine model GA-SVM can obtain higher accuracy rates when used for early warning in university learning.

• 대한산업공학회지
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• 제23권3호
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• pp.515-532
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• 1997

When balancing mixed model assembly lines (MMALs), workload smoothness should be considered on the model-by-model basis as well as on the station-by-station basis. This is because although station-by-station assignments may provide the equality of workload to workers, it causes the utilization of assembly lines to be inefficient due to the model sequences. This paper presents a genetic algorithm to improve the workload smoothness on both the station-by-station and the model-by-model basis in balancing MMALs. Proposed is a function by which the two kinds of workloads smoothness can be evaluated according to the various preferences of line managers. To enhance the capability of searching good solutions, our genetic algorithm puts emphasis on the utilization of problem-specific information and heuristics in the design of representation scheme and genetic operators. Experimental results show that our algorithm can provide better solutions than existing heuristics. In particular, our algorithm is outstanding on the problems with a larger number of stations or a larger number of tasks.

• Journal of Genetic Medicine
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• 제7권1호
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• pp.16-23
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• 2010

많은 내분비 질환이 유전적 요소를 갖고 있다. 단일 유전자 질환에서는 유전적 요인이 주요 원인이나 다인자성 질환에서는 환경과 생활습관 등이 함께 병인으로 작용한다. 유전성 내분비 질환의 분자유전학적 병인에 대한 이해에 대하여 최근 많은 발전이 있어 왔으며 분자유전학적 기술의 응용으로 질환에 대한 이해와 이를 이용한 진단 및 유전 상담에 도움이 되고 있다. 유전학적 검사로 특정 질환의 돌연변이를 증명하는 것은 진단이 모호한 경우에서 정확한 진단과 산전 진단, 보인자 검사에 적용될 수 있다. 그러나 유전자 검사만으로 임신 중절과 관련된 산전 진단에 이용하는 데에는 신중을 기해야 한다.

• 한국컴퓨터정보학회논문지
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• 제10권6호
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• pp.279-286
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• 2005

본 연구에서는 캐피탈시장에서의 고객신용예측을 위한 모형으로 여러 가지 인공신경망(Neural Network) 모형들을 유전자 알고리즘(Genetic Algorithm)을 이용하여 통합한 신용예측모형을 제안하였다. 10개의 학습된 인공신경망 모형들을 유전자알고리즘을 이용하여 종류별로 통합하여 MLP (Multi-Layered Perceptron), Linear, RBF(Radial Basis Function) 세 가지의 대표모델을 얻고 이를 다시 하나의 인공신경망 모델로 통합하였다. 이를 통합되기 이전의 각각의 인공신경망 모형들과 성능을 비교, 분석하여 본 연구에서 제안한 통합모형의 유효성과 통합방법의 타당성을 제시하였다.

• Journal of Interdisciplinary Genomics
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• 제3권1호
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• pp.13-20
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• 2021

Developmental and epileptic encephalopathies are the most devastating early-onset epilepsies, characterized by early-onset seizures that are often intractable, electroencephalographic abnormalities, developmental delay or regression, and various comorbidities. A large number of underlying genetic variants of developmental and epileptic encephalopathies have been identified over the past few decades. However, the most thorough sequencing studies leave 60-65% of patients without a molecular diagnosis. This review explores the genetic basis of developmental and epileptic encephalopathies that start within the first year of life, including Ohtahara syndrome, early myoclonic encephalopathy, epilepsy of infancy with migrating focal seizures, infantile spasms, and Dravet syndrome. The purpose of this review is to give an overview and encourage the clinicians to start considering genetic testing as an important investigation along with electroencephalogram for better understanding and management of developmental and epileptic encephalopathies.

• 한국독성학회:학술대회논문집
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• 한국독성학회 2004년도 KSOT/KEMS fall annual meeting
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• pp.19-20
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• 2004

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1997년도 춘계학술대회 논문집
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• pp.501-507
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• 1997

Composite material has very excellent mechanical properties including tensile stress and specific strength. Especially impact loads may be expected in many of the engineering applications of it. The suitability of composite material for such applications is determined not only by the usual paramenters, but its impactor energy-absorbing properties. Composite material under impact load has poor mechanical behavior and so needs tailoring its structure. Genetic algorithms(GA) is probabilistic optimization technique by principle of natural genetics and natural selection and neural networks(NN) is useful for prediction operation on the basis of learned data. Therefore, This study presents optimization techniques on the basis of genetic algorithms and neural networks to minimum stiffness design of laminated composite material.

• The Korean Journal of Physiology and Pharmacology
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• 제25권1호
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• pp.1-14
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• 2021

Cardiovascular disease (CVD) accounts for approximately 30% of all deaths worldwide and its prevalence is constantly increasing despite advancements in medical treatments. Cardiac remodeling and dysfunction are independent risk factors for CVD. Recent studies have demonstrated that cardiac structure and function are genetically influenced, suggesting that understanding the genetic basis for cardiac structure and function could provide new insights into developing novel therapeutic targets for CVD. Regular exercise has long been considered a robust nontherapeutic method of treating or preventing CVD. However, recent studies also indicate that there is inter-individual variation in response to exercise. Nevertheless, the genetic basis for cardiac structure and function as well as their responses to exercise training have yet to be fully elucidated. Therefore, this review summarizes accumulated evidence supporting the genetic contribution to these traits, including findings from population-based studies and unbiased large genomic-scale studies in humans.

• 대한수학교육학회지:수학교육학연구
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• 제11권2호
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• pp.351-362
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• 2001

Piaget's genetic epistemology has been known as the basis of the 'New Math' and as the opposite point of view to the historico-genetic principle. But these days Piaget's theory is considered to support the historico-genetic principle so that it influences many studies. This study shows the reason of the difference of interpretations of Piaget's theory.