• Journal of the Korean Society for Precision Engineering
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• v.15 no.3
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• pp.119-126
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• 1998

유리섬유 강화 열가소성 복합재료는 고상성형법에 의해 저렴한 가격으로 큰 부피의 제품의 제조에 널리 사용될 수 있어 아주 좋은 전망을 가지고 있다. 그러나 이러한 재료의 성형성이나 재료거동의 특성은 아직 잘 파악되지 않았다. 본 연구의 주안점은 이러한 재료의 단순 굽힘에서의 굽힘성형성을 연구하는데 두었다. 실험에 사용된 재료는 임의의 방향으로 위치한 유리섬유를 중량비로 20 %, 35 %, 40 % 함유한 폴리프로필렌이다 굽힘시험은 75 $^{\circ}C$에서 150 $^{\circ}C$ 사이의 온도에서 25 $^{\circ}C$ 씩 증가하면서 행했고, 편치속도는 2.54 mm/sec와 0.0254 mm/sec에서 행했다. 단순 굽힘시험에서 측정된 굽힘성형성은 해석적 모델로 예측한 결과와 비교하였다. 실험결과와 예측결과가 비교적 잘 일치함을 보였으며, 굽힘성 map으로써 성형 온도와 펀치반경의 좌굴에 대한 효과를 가시화 함은 물론 좋은 성형조건을 선정할 수 있는 좋은 도구로써 나타내었다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2002.05a
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• pp.305-309
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• 2002

In this paper, we present a standard S/W solution for nursery administration. This S/W would substitute for classical nonscientific nursery management that has depended on personal experience and intuition. Especially, the suggest S/W based on its early model(Hwangkum-a-jang) is designed to operate on its daily diary writing. It means every statistical data and information for a sales can be calculated by self analyzing function just by keeping a diary.

• Proceedings of the Korea Information Processing Society Conference
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• 2010.11a
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• pp.471-473
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• 2010

본 논문은 선형회귀(LR: Linear Regression)와 국부적인 방사기저함수 네트워크(RBFN: Radial Basis Function Networks)를 결합한 점진적인 모델(incremental model)의 설계와 관련되어진다. 전형적인 RBFN에 의한 모델링과는 달리, 제안된 방법의 근본적인 원리는 두 단계에 의해 고려되어진다. 첫째, 전체 모델의 설계과정에서 전역적인 모델로써 선형회귀에 의해 데이터의 선형부분을 구축한다. 다음으로, 모델링 오차는 오차가 존재하는 국부적인 공간에서 RBFN에 의해 보상되어진다. 여기서, 오차의 분포로부터 RBFN을 설계하기 위해 컨텍스트 기반 퍼지 클러스터링(CFC: Context-based Fuzzy Clustering)를 통해 정보입자의 형태로 구축되어진다. 실험은 자동차 mpg 연료소비량 예측과 부동산 가격예측문제를 통해 제안된 방법의 우수성을 증명한다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2023.01a
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• pp.341-342
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• 2023

배터리 기술 고도화 및 기술표준 강화에 따라 완성차 제조사와 배터리 업계간 활발한 협업이이어질 전망이다. 또한 기존 배터리 제조사들이 활발한 증설 및 밸류 체인 확장을 통한 기술가격 경쟁력 격차 유지에 적극적으로 나서고 있어, 향후 시장 주도권 경쟁이 가속화될 것으로 전망된다. 배터리의 온도 상승은 배터리 효율을 낮추는 원인이며, 배터리 온도 제어가 전기자동차 차량의 전체 성능 향상에 중요한 부분이라고 할 수 있다. 본 연구는 실제 Battery Pack 실험 전 열유동해석을 통해 배터리온도 상승추이 및 냉각효율 검증을 진행하는 과정에서 발생하는 과도한 시간 소요를 줄이기 위해 Machine Learning 을 활용하여 검증 효율 및 설계 효율을 높이는데 그 목적이 있으며, CFD를 활용한 배터리 효율 최적화 설계를 하는 기존 모델 대비 30%~50%정도의 성능향상을 예측할 수 있다.

• Journal of Energy Engineering
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• v.22 no.4
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• pp.370-375
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• 2013

This paper attempts to estimate the city gas demand function in Korea over the period 1981-2012. As the city gas demand function provides us information on the pattern of consumer's city gas consumption, it can be usefully utilized in predicting the impact of policy variables such as city gas price and forecasting the demand for city gas. We apply lagged dependent variable model and ordinary least square method as a robust approach to estimating the parameters of the city gas demand function. The results show that short-run price and income elasticities of the city gas demand are estimated to be -0.522 and 0.874, respectively. They are statistically significant at the 1% level. The short-run price and income elasticities portray that demand for city gas is price- and income-inelastic. This implies that the city gas is indispensable goods to human-being's life, thus the city gas demand would not be promptly adjusted to responding to price and/or income change. However, long-run price and income elasticities reveal that the demand for city gas is price- and income-elastic in the long-run.

• The Korean Journal of Financial Management
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• v.23 no.1
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• pp.49-67
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• 2006

This study examines whether won/dollar futures have price discovery function and volatility spillover effect or not, using intraday won/dollar futures prices, volumes, and spot rates for the interval from March 2, 2005 through May 30, 2005. Futures prices and spot rates are non-stationary, but there is the cointegration relationship between two time series. Futures returns, spot returns, and volumes are stationary. Asymmetric effects on volatility in futures returns and spot returns does not exist. Analytical results of mean equations of the BGARCH-EC (bivariate GARCH-error correction) model show that the increase of futures returns raise spot returns after 5 minutes, which implies that futures returns lead spot returns and won/dollar futures have price discovery function. In addition, the long-run equilibrium relationship between the two returns could help forecast spot returns. Analytical results of variance equations indicate that short-run innovations in the futures market positively affect the conditional variances of spot returns, that is, there is the volatility spillover effect in the won/dollar futures market. A dummy variable of volumes does not have an effect on two returns but influences significantly on two conditional variances.

• Journal of Energy Engineering
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• v.22 no.3
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• pp.245-249
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• 2013

This paper attempts to estimate the kerosene demand function in Korea over the period 1981-2012. As the kerosene demand function provides us information on the pattern of consumer's kerosene consumption, it can be usefully utilized in predicting the impact of policy variables such as kerosene price and forecasting the demand for kerosene. We apply least absolute deviations and least median squares estimation methods as a robust approach to estimating the parameters of the kerosene demand function. The results show that short-run price and income elasticities of the kerosene demand are estimated to be -0.468 and 0.409, respectively. They are statisitically significant at the 1% level. The short-run price and income elasticities portray that demand for kerosene is price- and income-inelastic. This implies that the kerosene is indispensable goods to human-being's life, thus the kerosene demand would not be promptly adjusted to responding to price and/or income change. However, long-run price and income elasticities reveal that the demand for kerosene is price- and income-elastic in the long-run.

• Current Research on Agriculture and Life Sciences
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• v.4
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• pp.141-153
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• 1986

This study intends to document the existing cyclical fluctuations of garic and onion price at farm gate level during the period of 1966-1986 in Korea. The existing patterns of such cyclical fluctuations were estimated systematically by removing the seasonal fluctuation and irregular movement as well as secular trend from the original price through the moving average method. It was found that the cyclical fluctuations of garic and onion prices repeated six and seven times respectively during the same period, also the amplitude coefficient of cyclical fluctuations showed speed up in recent years. It was noticed that the cyclical fluctuations of price in onion was higher than that of in garic.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.4
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• pp.391-404
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• 2021

This study developed a long-term prediction model for the potential yield of garlic based on a genetic algorithm (GA) by utilizing global climate reanalysis data. The GA is used for digging the inherent signals from global climate reanalysis data which are both directly and indirectly connected with the garlic yield potential. Our results indicate that both deterministic and probabilistic forecasts reasonably capture the inter-annual variability of crop yields with temporal correlation coefficients significant at 99% confidence level and superior categorical forecast skill with a hit rate of 93.3% for 2 × 2 and 73.3% for 3 × 3 contingency tables. Furthermore, the GA method, which considers linear and non-linear relationships between predictors and predictands, shows superiority of forecast skill in terms of both stability and skill scores compared with linear method. Since our result can predict the potential yield before the start of farming, it is expected to help establish a long-term plan to stabilize the demand and price of agricultural products and prepare countermeasures for possible problems in advance.

• Proceedings of the Technology Innovation Conference
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• 2003.02a
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• pp.173-190
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• 2003

Demand forecasting is essential in establishing national and corporate strategy as well as the management of their resource. We forecast demand for multi-generation product using discrete choice model combining diffusion model The discrete choice model generally captures consumers'valuation of the product's qualify in the framework of a cross-sectional analysis. We incorporate diffusion effects into a discrete choice model in order to capture the dynamics of demand for multi-generation products. As an empirical application, we forecast demand for worldwide DRAM (dynamic random access memory) and each of its generations from 1999 to 2005. In so doing, we use the method of 'Technological Forecasting'for DRAM Density and Price of the generations based on the Moore's law and learning by doing, respectively. Since we perform our analysis at the market level, we adopt the inversion routine in using the discrete choice model and find that our model performs well in explaining the current market situation, and also in forecasting new product diffusion in multi-generation product markets.