• ETRI Journal
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• v.33 no.1
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• pp.39-49
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• 2011

A new structure learning approach for Bayesian networks based on asexual reproduction optimization (ARO) is proposed in this paper. ARO can be considered an evolutionary-based algorithm that mathematically models the budding mechanism of asexual reproduction. In ARO, a parent produces a bud through a reproduction operator; thereafter, the parent and its bud compete to survive according to a performance index obtained from the underlying objective function of the optimization problem: This leads to the fitter individual. The convergence measure of ARO is analyzed. The proposed method is applied to real-world and benchmark applications, while its effectiveness is demonstrated through computer simulations. Results of simulations show that ARO outperforms genetic algorithm (GA) because ARO results in a good structure and fast convergence rate in comparison with GA.

• Steel and Composite Structures
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• v.15 no.4
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• pp.451-466
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• 2013

This paper deals with the multi-objective optimization of tire reinforcement structures such as the tread belt and the carcass path. The multi-objective functions are defined in terms of the discrete-type design variables and approximated by artificial neutral network, and the sensitivity analyses of these functions are replaced with the iterative genetic evolution. The multi-objective optimization algorithm introduced in this paper is not only highly CPU-time-efficient but it can also be applicable to other multi-objective optimization problems in which the objective function, the design variables and the constraints are not continuous but discrete. Through the illustrative numerical experiments, the fiber-reinforced tire belt structure is optimally tailored. The proposed multi-objective optimization algorithm is not limited to the tire reinforcement structure, but it can be applicable to the generalized multi-objective structural optimization problems in various engineering applications.

• Proceedings of the KIEE Conference
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• 1997.07b
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• pp.739-742
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• 1997

This paper proposes the structure and parameter optimization technique of fuzzy neural networks using genetic algorithm. Fuzzy neural network has advantages of both the fuzzy inference system and neural network. The determination of the optimal parameters and structure of the fuzzy neural networks, however, requires special efforts. To solve these problems, we propose a new learning method for optimization of fuzzy neural networks using genetic algorithm. It can optimize the structure and parameters of the entire fuzzy neural network globally. Numerical example is provided to show the advantages of the proposed method.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1999.10a
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• pp.301-308
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• 1999

This paper describes the application of genetic algorithm(GA) in the discrete optimal design of truss structures. Stochastic processes generate an intial population of design and then apply principles of natural selection/survival of the fittest to improve the design. GA is applied to minimum weight of truss subject to stress and displacement constraints under multiple loading conditions. First, optimum solutions obtained from GA are compared to verify the reliability of GA with m well-known transmission tower structure which is referred to by other authors. Then, discrete optimal design is performed in satisfying service conditions of truss structure with commercially available fabricated sizes. From the results, it is found that GA search technique is very effective for discrete optimal design of truss structure and has high robustness.

• Proceedings of the IEEK Conference
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• 2002.07c
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• pp.1650-1653
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• 2002

In this paper, we propose the initial optimized structure of the Radial Basis function Networks that is simple in the part of the structure and fast converges more than neural networks with the analysis method using Time- Frequency Localization. We construct the hidden node with the Radial Basis functions their localization are similar with approximation target function in the plane of the Time and Frequency. We finally make a good decision of the initial structure for function approximation using genetic algorithm

• International Journal of Industrial Entomology and Biomaterials
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• v.24 no.1
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• pp.41-47
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• 2012

The Scarites aterrimus (Coleoptera: Carabidae) dwells exclusively on coastal sandy dunes. Previously, we investigated the nation-wide magnitude and nature of genetic diversity of the species using mitochondrial COI gene and found moderate to low magnitude of sequence diversity, the presence of closely related haplotypes, and relatively high gene flow estimate. Based on these observations we concluded that the species had no historical barriers that bolster genetic subdivision and possible population decline. In this study, we additionally sequenced mitochondrial COII gene from 23 individuals collected from 9 Korean localities to confirm previous findings. Sequencing of 688 bp COII gene provided 5 haplotypes ranging in sequence divergence from 0.145% to 0.291% (1 ~ 2 bp), further confirming low sequence divergence of the species. Gene flow estimates and genetic diversity estimates also support the previous findings that there had been no historical barriers that bolster genetic subdivision.

• Korean Journal of Pharmacognosy
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• v.25 no.4 s.99
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• pp.395-398
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• 1994

A diterpene alkaloid in addition to hypaconitine and mesaconitine was isolated from the tubers of Aconitum napiforme (Ranunculaceae), which is an indigenous plant in Korea. Its structure was elucidated as 8-methoxy 14-benzoyl hypaconine by Physicochemical and spectroscopic data. This compound was isolated from this plant for the first time.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.254-254
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• 2000

This paper presents a genetic programming based evolutionary strategy for on-line adaptive learnable evolvable hardware. genetic programming can be useful control method for evolvable hardware for its unique tree structured chromosome. However it is difficult to represent tree structured chromosome on hardware, and it is difficult to use crossover operator on hardware. Therefore, genetic programming is not so popular as genetic algorithms in evolvable hardware community in spite of its possible strength. We propose a chromosome representation methods and a hardware implementation method that can be helpful to this situation. Our method uses context switchable identical block structure to implement genetic tree on evolvable hardware. We composed an evolutionary strategy (or evolvable hardware by combining proposed method with other's striking research results. Proposed method is applied to the autonomous mobile robots cooperation problem to verify its usefulness.

• Animal cells and systems
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• v.9 no.1
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• pp.27-35
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• 2005

Bupleurum euphorbioides is isolated and restricted to high mountains in Korea northeastern China. Its conservation depends on whether it is threatened by inbreeding or a loss of genetic diversity. We compared the genetic variability in B. euphorbioides with B. longiradiatum, a widespread congener, to understand how they differ in their population genetic structure. Although B. euphorbioides showed a little lower genetic variability than B. longiradiatum, $F_{IS}$ statistics for most loci were strongly positive in both B. euphorbioides (0.445) and B. longiradiatum (0.553). In addition, B. euphorbioides showed higher mean $F_{ST}$ value than B. longiradiatum (0.297 vs 0.194). It might be due to the polycarpic nature of B. longiradiatum, which holds higher genetic potentials effectively in homogeneous environment than the monocarpic B. euphorbioides. The results suggested that B. euphorbioides is a genetically viable species, and that they are threatened primarily by environmental factor.

• Proceedings of the Korean Society of Fisheries Technology Conference
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• 2001.05a
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• pp.559-560
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• 2001

The objective of the present study was to analyze genetic variation and characteristics in rainbow trout(Oncorhynchus mykiss) using amplified fragment length polymorphism(AFLP) method as molecular genetic technique, to evaluate the usefulness of AFLP as genetic markers, and to compared the efficiency of agarose and polyacrylamide sequencing gels. The amplified products were performed by agarose and sequencing gel electrophoresis to detect AFLP band patterns, respectively. Using 9 primer combinations, total of 141 AFLP bands were produced, 108 bands(82.4％) of which were polymorphic in agarose gels. In sequencing gels, total of 288 bands were generated, and 220 bands (76.4％) were polymorphic. The level of bandsharing(BS) ranged from 0.18 to 0.32 for the 9 primer combinations tested, with a mean of 0.24. Consequently, AFLP markers of these rainbow trout could be used as genetic information such as species identification, genetic relationship or analysis of genome structure, and selection aids for genetic improvement of economically importment traits in fish species.