• International Journal of Advanced Culture Technology
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• 제11권2호
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• pp.358-365
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• 2023

As the Internet is used as a major channel for marketing and sales, the top ranking of search engine results is becoming a key competitor among websites. Various methods exist to maintain the top ranking of websites in search engines, typically investing heavily in organic coding or search engine optimization. The purpose of this paper, we present the ranking by recognizing factors that should be removed as negative factors when designing a web page in consideration of website visibility (SEO) because if website visibility is not met, the ranking may fall behind or be completely removed from the search engine index. The experiments that recognized and ranked the negative factors of website visibility proposed in this paper were provided through theory and experiments based on the existing website visibility analysis model. The models analyzed in this paper, we expressed or quantified as scores based on the methodology of each model, and 10 items were selected as negative factors through experiments and ranked as high scores. Therefore, when designing a website, it should be considered that the website is not removed from the search engine index as it is designed by excluding high-ranking items, which are negative factors.

• Journal of Mechanical Science and Technology
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• 제20권3호
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• pp.366-375
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• 2006

In this paper, it is intended to introduce a method to solve multi-objective optimization problems and to evaluate its performance. In order to verify the performance of this method it is applied for a vertical roller mill for Portland cement. A design process is defined with the compromise decision support problem concept and a design process consists of two steps: the design of experiments and mathematical programming. In this process, a designer decides an object that the objective function is going to pursuit and a non-linear optimization is performed composing objective constraints with practical constraints. In this method, response surfaces are used to model objectives (stress, deflection and weight) and the optimization is performed for each of the objectives while handling the remaining ones as constraints. The response surfaces are constructed using orthogonal polynomials, and orthogonal array as design of experiment, with analysis of variance for variable selection. In addition, it establishes the relative influence of the design variables in the objectives variability. The constrained optimization problems are solved using sequential quadratic programming. From the results, it is found that the method in this paper is a very effective and powerful for the multi-objective optimization of various practical design problems. It provides, moreover, a reference of design to judge the amount of excess or shortage from the final object.

• 대한기계학회논문집A
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• 제32권3호
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• pp.258-266
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• 2008

The conventional approximate optimization method, which uses the statistical design of experiments(DOE) and response surface method(RSM), can derive an approximated optimum results through the iterative process by a trial and error. The quality of results depends seriously on the factors and levels assigned by a designer. The purpose of this study is to propose a new technique, which is called a sequential design of experiments(SDOE), to reduce a trial and error procedure and to find an appropriate condition for using artificial neural network(ANN) systematically. An appropriate condition is determined from the iterative process based on the analysis of means. With this new technique and ANN, it is possible to find an optimum design accurately and efficiently. The suggested algorithm has been applied to various mathematical examples and a structural problem.

• 한국기계가공학회지
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• 제14권3호
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• pp.85-91
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• 2015

The press-fit shaft is an important part used in automobiles, vessels, and trains. This study proposes an optimized design method to reduce damage that may occur in the press-fitted shaft by modifying the shape of the boss step of the press-fitted shaft. To reduce the time and cost of running the optimized design method, an approximate design optimization is applied and an optimized algorithm is generated using a genetic algorithm that is widely used in engineering fields and an approximate model using a response surface method. The planned experiments for the data that are needed to generate the approximate model use a central composite design (CCD) and Latin hypercube sampling (LHS), and the results of the approximate optimization using the above two design of experiments are to be compared.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2001년도 춘계학술대회논문집C
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• pp.339-344
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• 2001

In recent engineering, the designer has become more and more dependent on the computer simulations such as FEM (Finite Element Method) and BEM (Boundary Element Method). In order to optimize such implicit models more efficiently and reliably, the meta-modeling technique has been developed for solving such a complex problems combined with the DACE (Design and Analysis of Computer Experiments). It is widely used for exploring the engineer's design space and for building meta-models in order to facilitate an effective solution of multi-objective and multi-disciplinary optimization problems. Optimization of a train suspension is performed according to the minimization of forty-six responses that represent ten ride comforts, twelve derailment quotients, twelve unloading ratios, and twelve stabilities by using the Kriging meta-model of a train suspension. After each Kriging meta-model is constructed, multi-objective optimal solutions are achieved by using a nonlinear programming method called SQP (Sequential Quadratic Programming).

• 동력기계공학회지
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• 제17권6호
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• pp.149-155
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• 2013

Since bio-diesel oil has a merit that it satisfies both demand of substitution for fossil fuel and reduction in carbon dioxide emission, it is widely used in diesel engines by blending in gas oil in small quantity. It is needed to reduce in NOx emission in some way or others if blending ratio of bio-diesel oil is going to increase, because it is demerit that bio-diesel oil emits more NOx emission than gas oil. In this study, it was accomplished to optimize 3 factors what effect on NOx emission as blending ratio of bio-diesel oil, injection timing and common rail pressure with an introduction of a design of experiments, in order to minimize a number of tests. It was cleared that to introduce the design of experiments was very available in NOx optimization.

• Nuclear Engineering and Technology
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• 제53권1호
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• pp.208-215
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• 2021

Cosmic-ray muon scattering tomography (MST) technology is a new radiation imaging technology with unique advantages. As the performance of its image reconstruction algorithm has a crucial influence on the imaging quality, researches on this algorithm are of great significance to the development and application of this technology. In this paper, a fast inspection algorithm based on clustering analysis for the identification of the existence of nuclear materials is studied and optimized. Firstly, the principles of MST technology and a binned clustering algorithm were introduced, and then several simulation experiments were carried out using Geant4 toolkit to test the effects of exposure time, algorithm parameter, the size and structure of object on the performance of the algorithm. Based on these, we proposed two optimization methods for the clustering algorithm: the optimization of vertical distance coefficient and the displacement of sub-volumes. Finally, several sets of experiments were designed to validate the optimization effect, and the results showed that these two optimization methods could significantly enhance the distinguishing ability of the algorithm for different materials, help to obtain more details in practical applications, and was therefore of great importance to the development and application of the MST technology.

• 대한기계학회논문집A
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• 제24권3호
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• pp.661-666
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• 2000

Optimization of the elastic joint of train is performed according to the minimization of ten responses which represent driving safety and ride comfort of train and analyzed by using the each response se surface model from stochastic design of experiments. After the each response surface model is constructed, the main effect and sensitivity analyses are successfully performed by 2nd order approximated regression model as described in this paper. We can get the optimal solutions using by nonlinear programming method such as simplex or interval optimization algorithms. The response surface models and the optimization algorithms are used together to obtain the optimal design of the elastic joint of train. the ten 2nd order polynomial response surface models of the three translational stiffness of the elastic joint (design factors) are constructed by using CCD(Central Composite Design) and the multi-objective optimization is also performed by applying min-max and distance minimization techniques of relative target deviation.

• 정보처리학회논문지D
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• 제17D권3호
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• pp.175-184
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• 2010

최근 DNA 칩의 등장으로 유전자 관련 실험과 연구가 매우 용이해졌으며 이를 활용한 다양한 실험 결과로 대량의 데이터가 제공되고 있다. DNA칩에 의해 제공된 데이터는 2차원 행렬로 표현되며 하나의 축은 유전자를 나타내고 다른 하나의 축은 샘플정보를 나타낸다. 이러한 데이터에 대하여 빠른 시간 안에 좋은 품질의 군집화를 수행함으로써 이후의 분석 단계인 분류화 작업의 정확도와 효율성을 높일 수 있다. 본 논문에서는 생태계 모방 알고리즘의 하나인 Particle Swarm Optimization 알고리즘을 사용하여 방대한 양의 DNA칩 데이터에 대한 효율적인 군집화 기법을 제안하였으며 실험을 통해서 PSO 기반의 군집화 알고리즘이 기존의 군집화 알고리즘들보다 수행속도 및 품질 면에서 우수한 성능을 가짐을 보였다.

• 한국연소학회:학술대회논문집
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• 한국연소학회 2014년도 제49회 KOSCO SYMPOSIUM 초록집
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• pp.141-142
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• 2014

This numerical study was carried out to optimize dual fuel combustion on natural gas-diesel in static chamber. Spray experiments conducted under conditions of premixed methan 0%, 5% and 10%. In the results, penetration decreases when premixed methane is increasing. Constants of numerical models were acquired from results of spray experiments to enhance accuracy of numerical study. And dual fuel engine simulation was implemented by using AVL-FIRE with acquired constants.