• Journal of Astronomy and Space Sciences
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• 제32권1호
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• pp.39-44
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• 2015

It is well known that the space radiation dose over the polar route should be carefully considered especially when the space weather shows sudden disturbances such as CME and flares. The National Meteorological Satellite Center (NMSC) and Korea Astronomy and Space Science Institute (KASI) recently established a basis for a space radiation service for the public by developing a space radiation prediction model and heliocentric potential (HCP) prediction model. The HCP value is used as a critical input value of the CARI-6 and CARI-6M programs, which estimate the aviation route dose. The CARI-6/6M is the most widely used and confidential program that is officially provided by the U.S. Federal Aviation Administration (FAA). The HCP value is given one month late in the FAA official webpage, making it difficult to obtain real-time information on the aviation route dose. In order to overcome this limitation regarding time delay, we developed a HCP prediction model based on the sunspot number variation. In this paper, we focus on the purpose and process of our HCP prediction model development. Finally, we find the highest correlation coefficient of 0.9 between the monthly sunspot number and the HCP value with an eight month time shift.

• 한국콘텐츠학회논문지
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• 제20권12호
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• pp.49-57
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• 2020

본 연구는 우리나라 수출 분야 산업의 경쟁력을 나타내는 부가가치율을 다양한 머신러닝 기법을 활용하여 예측하였다. 아울러, 예측의 정확성 및 안정성을 높이기 위하여 머신러닝 기법 예측값들에 예측조합 기법을 적용하였다. 특히, 본 연구는 산업별 부가가치율에 영향을 주는 다양한 변수를 고려하기 위하여 재귀적특성제거 방법을 사용하여 주요 변수를 선별한 후 머신러닝 기법에 적용함으로써 예측과정의 효율성을 높였다. 분석결과, 예측조합 방법에 따른 예측값은 머신러닝 기법 예측값들보다 실제의 산업 부가가치율에 근접한 것으로 나타났다. 또한, 머신러닝 기법의 예측값들이 큰 변동성을 보이는 것과 달리 예측조합 기법은 안정적인 예측값을 나타내었다.

• International Journal of Internet, Broadcasting and Communication
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• 제10권1호
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• pp.61-64
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• 2018

In this paper, a pixel value prediction algorithm using edge components in three directions is proposed. There are various directional edges and similarity between adjacent pixels in natural images. After detecting the edge components in the x-axis direction, the y-axis direction, and the diagonal axis direction, the pixel value is predicted by applying the detected edge components and similarity between neighboring pixels. In particular, the predicted pixel value is calculated according to the intensity of the edge component in the diagonal axis direction. Experimental results show that the proposed algorithm can effectively predict pixel values. The proposed algorithm can be used for applications such as reversible data hiding, reversible watermarking to increase the number of embedded data.

• 한국건축시공학회지
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• 제8권5호
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• pp.119-125
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• 2008

In this paper, the estimation of super retarding concrete incorporating mineral admixtures at the same time including fly ash(FA), blast furnace slag(BS) are studied based on maturity method. The setting time was retarded, as super retarding agent contents increase and curing temperature decreases. In addition, apparent activation energy by Arrhenius function was ranged from $24\sim35$ KJ/mol with slightly difference along with mixture proportion. This value is smaller than existing value $30\sim50$ KJ/mol. Based on strength development estimation. it exhibited comparable relativity between prediction value and measurement value. Therefore, this study provided effective strength development prediction value with super retarding agent contents and mineral admixture combination. Strength development prediction equation provided herein is possibly valid for estimating accurate strength development of the super retarding concrete at the job site.

• 한국정보과학회논문지:시스템및이론
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• 제28권11호
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• pp.592-600
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• 2001

슈퍼스칼라 프로세서는 성능향상을 위해 명령어 반입폭과 이슈율을 증가시키고 있다. 데이터 종속성은 ILP(Instruction-Level Parallelism)를 향상시키는데 주요 장애요소가 되고 있으며, 최근 여러 논문에서 데이터 종속성을 제거하기 위해서 명령어의 결과값을 예상하는 메커니즘이 연구되었다. 그러나 이러한 예측기들은 예상한 명령어의 실제 결과값으로 예상 테이블을 갱신하기 전에 그 명령어를 다시 예상할 때 부적절(stale)한 데이터를 사용함으로써 예상 실패율이 증가하여 프로세서의 성능을 감소시킨다. 본 논문에서는 부적절 데이터 사용을 줄여 높은 성능을 얻을 수 있는 새로운 하이브리드 예측 메커니즘을 제안한다. 제안된 하이브리드 결과값 예측기는 예상 테이블을 모험적으로 갱신할 수 있기 때문에 부적절 데이터로 인해 잘못 예상되는 명령어의 수를 효과적으로 감소시킨다. 16-이슈폭 슈퍼스칼라 프로세서에서 SPECint95 벤치마크 프로그램에 대해 모험적 갱신을 사용함으로써 모험적 갱신을 사용하지 않은 경우의 평균 예상 정확도 59%에 비해 평균 예상 정확도가 72%에 비해 평균 예상 정확도가 72%로 크게 향상되었다.

• 한국컴퓨터정보학회논문지
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• 제10권2호
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• pp.87-95
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• 2005

고성능 마이크로프로세서에서 값 예측기는 한 명령어의 결과를 미리 예측하여 명령들 간의 데이터 종속관계를 극복하고 실행함으로써 명령어 수준 병렬성(Instruction Level Parallelism, ILP)을 향상시키는 기법이다. 본 논문에서는 ILP 프로세서 명령어 수준 병렬성의 성능향상을 위하섞 값을 미리 예측하여 병렬로 이슈하고 수행하는 값 예측기를 비교 분석하여 각 테이블 갱신 시점에 따른 예측기별 평균 성능향상과 예측률 및 예측정확도를 측정하여 평가한다 이러한 타당성을 검증하기 위해 실행구동방식 시뮬레이터를 사용하여 SPECint95 벤치마크를 시뮬레이션하여 비교한다.

• 한국소음진동공학회논문집
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• 제23권4호
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• pp.295-300
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• 2013

The noise map can be applied to predict the effect of noise and establish the noise reduction measure. But the predicted value in the noise map can vary depending on the input variables. Thus, we surveyed the several prediction models and analyzed the changes corresponding to the variables for obtaining the coherency and accuracy of prediction results. As a result, we know that the Schall03 and CRN model can be applied to predict the railway noise in Korea and the correction value, such as bridges correction, multiple reflection correction, curve correction must be used for reflecting the condition of the prediction site. Also, we know that the prediction guideline is an essential prerequisite in order to obtain the unified and accurate predicted value for railway noise.

• Journal of Advanced Marine Engineering and Technology
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• 제39권8호
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• pp.828-832
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• 2015

This study is conducted for the evaluation of corrosion and lifetime prediction of fire extinguishing pipelines in residential buildings. The fire extinguishing pipeline is made of carbon steel. Twenty-four samples were selected among all the fire extinguishing pipelines in a building; the selection was based on specimenspositions, pipeline diameters, and pipeline thickness. Analysis was conducted by using the results of visual inspection, electrochemical potentiodynamic anodic polarization test, pitting depth measurements, and extreme value statistics with the Gumbel distribution. The maximum pitting depth and remaining life were statistically predicted using extreme value statistics. During visual inspection, pitting corrosion was observed in several samples. In addition, extreme value statistics demonstrated that there were several pipelines that were very sensitive to pitting corrosion. However, the pitting corrosion was not critical in all the pipelines; thus, it was necessary to change only those pipelines that were severely corroded.

• 한국정보처리학회논문지
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• 제7권5호
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• pp.1419-1425
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• 2000

When we predict of software reliability, we can't know the testing stopping time and how many faults be residues in software the (the maximum value of data) during these software testing process, therefore we assume the maximum value and the training result can be inaccuracy. In this paper, we present neural network approach for software reliability prediction with unnormalized (actual or original collected) data. This approach is not consider the maximum value of data and possible use the network without normalizing but the predictive accuracy is better. Also, the unnormalized method shows better predictive accuracy than the normalized method given by maximum value. Therefore, we can make the best use of this model in software reliability prediction using unnormalized data.

• 전기학회논문지
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• 제59권12호
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• pp.2202-2211
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• 2010

The wind power prediction system is composed of a meteorological forecasting module, calculation module of wind power output and HMI(Human Machine Interface) visualization system. The final information from this system is a short-term (6hr ahead) and mid-term (48hr ahead) wind power prediction value. The meteorological forecasting module for wind speed and direction forecasting is a combination of physical and statistical model. In this system, the WRF(Weather Research and Forecasting) model, which is a three-dimensional numerical weather model, is used as the physical model and the GFS(Global Forecasting System) models is used for initial condition forecasting. The 100m resolution terrain data is used to improve the accuracy of this system. In addition, optimization of the physical model carried out using historic weather data in Jeju. The mid-term prediction value from the physical model is used in the statistical method for a short-term prediction. The final power prediction is calculated using an optimal adjustment between the currently observed data and data predicted from the power curve model. The final wind power prediction value is provided to customs using a HMI visualization system. The aim of this study is to further improve the accuracy of this prediction system and develop a practical system for power system operation and the energy market in the Smart-Grid.