• 지능정보연구
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• 제18권4호
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• pp.43-57
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• 2012

제조업에 있어서 판매 후 서비스 건수와 내용 등은 향후 서비스 제공을 위한 자원배분의 효율성 증진과 서비스 품질 향상을 위해서도 매우 중요한 정보이다. 따라서 기업들은 향후 발생하는 판매 후 서비스에 대해 정확히 예측하고 그에 따라 적절히 대처하는 능력을 확보할 필요성이 제조업을 중심으로 증가하고 있다. 그러나 실제로 이들 기업들이 활용하고 있는 서비스 수요예측 방법들은 전통적인 통계적인 예측기법이거나, 시뮬레이션을 기반한 기법들이다. 예를 들면, 전통적인 통계적인 예측기법으로는 회귀분석(regression analysis)의 경우, 다양한 제품모델에 대한 판매 후 서비스 발생 패턴이 선형적인 관계가 매우 적음에도 불구하고 선형으로 가정하여 추정한다는 점과 적정한 회귀식을 가정하여야 되며, 이러한 가정이 실제 경영환경에서는 매우 어렵다는 점 등이 기존의 예측기법들의 한계점으로 지적되고 있다. 본 연구에서는 디지털 TV 모델을 생산 판매 하는 A사의 사례연구를 통하여 최근 인공지능연구에서 각광을 받고 있는 사례기반추론(case-based reasoning; CBR) 기법을 활용한 서비스 수요예측 프레임워크를 제안하고자 한다. 또한, 사례기반추론에서 핵심적인 역할 중 하나인 유사 사례추출 방법에 있어서 가장 일반적인 nearest-neighbor 방법 이외의 유사 사례추출 방법을 제안하고자 한다. 특히, 본 연구에서 제안하는 유사 사례추출 방법은 인공신경망(artificial neural network)을 활용한 자기조직화지도(Self-Organizing Maps : SOM) 군집화 기법을 활용한 유사 사례추출 방식으로 이를 활용한 서비스 수요예측 프레임워크에 구현하고, 실제 기업의 판매 후 서비스 데이터를 활용하여 본 연구에서 제안하는 서비스 수요 예측 프레임워크의 유효성을 실증적으로 검증하고자 한다.

• 지능정보연구
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• 제24권2호
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• pp.1-19
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• 2018

주가 예측은 학문적으로나 실용적으로나 중요한 문제이기에, 주가 예측에 관련된 연구가 활발히 진행되었다. 빅 데이터 시대에 도입하면서, 빅 데이터를 결합한 주가 예측 연구도 활발히 진행되고 있다. 다수의 데이터를 기반으로 기계 학습을 이용한 연구가 주를 이룬다. 특히 언론의 효과를 접목한 연구 방법들이 주목을 받고 있는데, 그중 온라인 뉴스를 분석하여 주가 예측에 활용하는 연구가 주를 이루고 있다. 기존 연구들은 온라인 뉴스가 개별 회사에 대한 미치는 영향을 주로 살펴보았다. 또한, 관련성이 높은 기업끼리 서로 영향을 주는 것을 고려하는 방법도 최근에 연구되고 있다. 이는 동질성을 가지는 산업군에 대한 효과를 살펴본 것인데, 기존 연구에서 동질성을 가지는 산업군은 국제 산업 분류 표준에 따른다. 즉, 기존 연구들은 국제 산업 분류 표준으로 나뉜 산업군이 동질성을 가진다는 가정하에서 분석을 시행하였다. 하지만 기존 연구들은 영향력을 가지는 회사를 고려하지 못한 채 예측하였거나 산업군 내에서 이질성이 존재하는 점을 반영하지 못했다는 한계점을 가진다. 본 연구는 산업군 내에 이질성이 존재함을 밝히고, 이질성을 반영하지 못한 기존 연구의 한계점을 K-평균 군집 분석을 적용하여, 주가에 영향을 미치는 산업군의 동질적인 효과를 반영할 수 있는 방법론을 제안하였다. 방법론이 적합하다는 것을 증명하기 위해 3년간의 온라인 뉴스와 주가를 통해 실험한 결과, 다수의 경우에서 본 논문에서 제시한 방법이 좋은 결과를 나타냄을 확인할 수 있었으며, 국제 산업 분류 표준 산업군 내에서 이질성이 클수록 본 논문에서 제시한 방법이 좋은 효과를 보인다는 것을 확인할 수 있었다. 본 연구는 국제 산업 분류 표준으로 나누어진 기업들이 높은 동질성을 가지지 않는 다는것을 밝히고 이를 반영한 예측 모형의 효율성을 입증하였다는 점에서 의의를 가진다.

• 한국의사학회지
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• 제18권2호
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• pp.197-227
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• 2005

Heojun was the top scientist on Medicine in the 16th and 17th centuries and wrote the Dongeubogam describing the top-level medical theory and technology. So far, his outlook on nature has been disregarded even though his medicine is still effective. Through this study, I would like to know if his outlook on nature as well as his medicine is still effective. The conclusions are as follows: 1. According to his output, the origin of the universe started from the spinning of One Gi(一氣) which is quite different from Hawking's theory. Hawking assumed that the origin of the universe started from the Big-bang and will end to the Big-crunch. However, the current report on the origin of a star is quite similar to Heojun's theory and we acknowledge that his view on the origin of the universe is still effective. 2. According to his output, the universe repeats expanding and contracting forever while Hawking assumed it will come to the end, the Big-crunch, based on the expanding universe theory. Some scientists assists that Hawking's assumption should have some contradictions. Now, we acknowledge that Heojun's universal cycling theory which corresponds with modern physical theories is still effective, which would lead to a new environmental movement. 3. His view on the structure of the universe is quite different from the output of the current science, which results from his thought that the nature should be reviewed from the point of human's view. His view on the structure will be able to be updated based on the output of the current science. 4. The universe analogy started from the East Asian area as well as the Greek and Roman area in the ancient. The idea has disappeared since the scientific revolution era in the West while the idea has been deepened and abundant in the East and has become one of the major philosophical bases. Heojun emphasized its importance from the beginning of his book. 5. The nation analogy has been popular all times and places. According to his output, governing a country is like controlling one's body. 6. According to Needham's output, the universe analogy and the nation analogy were based on the ancient developed alchemy. And Harper assumed that Taiosm was based on the macrobiotic hygiene which was developed by the ancient developed alchemists. We acknowledge that xian(仙) cult, macrobiotic hygiene, medicine, alchemy and the ancient philosophy started from our ancients. Heojun's output restored our ancient tradition by combining the macrobiotic hygiene and philosophy with medicine. 7. Roughly predicting yearly weather would be unacceptable by the current scientist but Heojun's yearly weather forecast is still used in the clinic and seems effective to prepare from any epidemic disease. 8. 'Day and Night' and Four seasons are the most important factors to the macrobiotic hygiene according to the Dongeubogam. The new environmental movements should be based on the most important factors, otherwise the human beings as well as the environment would fail to survive. 9. Wind, Coldness, Heat, Humidity, Dryness and Fire represents weather. The six weather factors represent one of six phases of a year which is decided by the areal factors. Heojun preferred the six factors generated in the body itself to them from the outside. He thought a human being was a universe and the six factors generated in the body responded to the factors of the outside. 10. According to his output, Heat and Humidity are the most important factors which make a human being ill. 11. Life span, disease, food, and dwelling are dependent upon the geographical feature, according to Heojun's output. In addition, one's appearance and his five viscera and the six entrails depend on the food as well as the geographical feature. 12. Heath is related with the environment and they effects upon each other. If one is weak, he will be deeply effected by the nature. On the other hand, if one is strong, he will effect on the nature. That's why people live together. 13. According to Heojun's work, the society is an important factor comprising the environment. During a peaceful era, the society becomes stable and human beings are stable as well while they will be on fire during a chaotic era. 14. Medicine deals with human beings who live in the nature, so any medical book cannot be excellent unless it has any description on the nature. Heojun's outlook on the nature turned out to be logical and suitable even from the point of the current view and it is still effective as if his clinical knowledge and technology are still effective. Something unsuitable may be substituted with the output of the current science.

• 지능정보연구
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• 제22권4호
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• pp.177-192
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• 2016

기계학습(Machine Learning)은 인공 지능의 한 분야로, 데이터를 이용하여 기계를 학습시켜 기계 스스로가 데이터 분석 및 예측을 하게 만드는 것과 관련한 컴퓨터 과학의 한 영역을 일컫는다. 그중에서 SVM(Support Vector Machines)은 주로 분류와 회귀 분석을 목적으로 사용되는 모델이다. 어느 두 집단에 속한 데이터들에 대한 정보를 얻었을 때, SVM 모델은 주어진 데이터 집합을 바탕으로 하여 새로운 데이터가 어느 집단에 속할지를 판단해준다. 최근 들어서 많은 금융전문가는 기계학습과 막대한 데이터가 존재하는 금융 분야와의 접목 가능성을 보며 기계학습에 집중하고 있다. 그러면서 각 금융사는 고도화된 알고리즘과 빅데이터를 통해 여러 금융업무 수행이 가능한 로봇(Robot)과 투자전문가(Advisor)의 합성어인 로보어드바이저(Robo-Advisor) 서비스를 발 빠르게 제공하기 시작했다. 따라서 현재의 금융 동향을 고려하여 본 연구에서는 기계학습 방법의 하나인 SVM을 활용하여 매매성과를 올리는 방법에 대해 제안하고자 한다. SVM을 통한 예측대상은 한국형 변동성지수인 VKOSPI이다. VKOSPI는 금융파생상품의 한 종류인 옵션의 가격에 영향을 미친다. VKOSPI는 흔히 말하는 변동성과 같고 VKOSPI 값은 옵션의 종류와 관계없이 옵션 가격과 정비례하는 특성이 있다. 그러므로 VKOSPI의 정확한 예측은 옵션 매매에서의 수익을 낼 수 있는 중요한 요소 중 하나이다. 지금까지 기계학습을 기반으로 한 VKOSPI의 예측을 다룬 연구는 없었다. 본 연구에서는 SVM을 통해 일 중의 VKOSPI를 예측하였고, 예측 내용을 바탕으로 옵션 매매에 대한 적용 가능 여부를 실험하였으며 실제로 향상된 매매 성과가 나타남을 증명하였다.

• Journal of Preventive Medicine and Public Health
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• 제16권1호
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• pp.135-152
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• 1983

Emergency medical service is an important part of the health care delivery system, and the optimal allocation of resources and their efficient utilization are essentially demanded. Since these conditions are the prerequisite to prompt treatment which, in turn, will be crucial for life saving and in reducing the undesirable sequelae of the event. This study, taking the hyperbaric chamber for carbon monoxide poisoning as an example, is to develop a stochastic approach for solving the problems of optimal allocation of such emergency medical facility in Korea. The hyperbaric chamber, in Korea, is used almost exclusively for the treatment of acute carbon monoxide poisoning, most of which occur at home, since the coal briquette is used as domestic fuel by 69.6 per cent of the Korean population. The annual incidence rate of the comatous and fatal carbon monoxide poisoning is estimated at 45.5 per 10,000 of coal briquette-using population. It offers a serious public health problem and occupies a large portion of the emergency outpatients, especially in the winter season. The requirement of hyperbaric chambers can be calculated by setting the level of the annual queueing rate, which is here defined as the proportion of the annual number of the queued patients among the annual number of the total patients. The rate is determined by the size of the coal briquette-using population which generate a certain number of carbon monoxide poisoning patients in terms of the annual incidence rate, and the number of hyperbaric chambers per hospital to which the patients are sent, assuming that there is no referral of the patients among hospitals. The queueing occurs due to the conflicting events of the 'arrival' of the patients and the 'service' of the hyperbaric chambers. Here, we can assume that the length of the service time of hyperbaric chambers is fixed at sixty minutes, and the service discipline is based on 'first come, first served'. The arrival pattern of the carbon monoxide poisoning is relatively unique, because it usually occurs while the people are in bed. Diurnal variation of the carbon monoxide poisoning can hardly be formulated mathematically, so empirical cumulative distribution of the probability of the hourly arrival of the patients was used for Monte Carlo simulation to calculate the probability of queueing by the number of the patients per day, for the cases of one, two or three hyperbaric chambers assumed to be available per hospital. Incidence of the carbon monoxide poisoning also has strong seasonal variation, because of the four distinctive seasons in Korea. So the number of the patients per day could not be assumed to be distributed according to the Poisson distribution. Testing the fitness of various distributions of rare event, it turned out to be that the daily distribution of the carbon monoxide poisoning fits well to the Polya-Eggenberger distribution. With this model, we could forecast the number of the poisonings per day by the size of the coal-briquette using population. By combining the probability of queueing by the number of patients per day, and the probability of the number of patients per day in a year, we can estimate the number of the queued patients and the number of the patients in a year by the number of hyperbaric chamber per hospital and by the size of coal briquette-using population. Setting 5 per cent as the annual queueing rate, the required number of hyperbaric chambers was calculated for each province and for the whole country, in the cases of 25, 50, 75 and 100 per cent of the treatment rate which stand for the rate of the patients treated by hyperbaric chamber among the patients who are to be treated. Findings of the study were as follows. 1. Probability of the number of patients per day follows Polya-Eggenberger distribution. $$P(X=\gamma)=\frac{\Pi\limits_{k=1}^\gamma[m+(K-1)\times10.86]}{\gamma!}\times11.86^{-{(\frac{m}{10.86}+\gamma)}}$$ when$${\gamma}=1,2,...,n$$$$P(X=0)=11.86^{-(m/10.86)}$$ when $${\gamma}=0$$ Hourly arrival pattern of the patients turned out to be bimodal, the large peak was observed in $7 : 00{\sim}8 : 00$ a.m., and the small peak in $11 : 00{\sim}12 : 00$ p.m. 2. In the cases of only one or two hyperbaric chambers installed per hospital, the annual queueing rate will be at the level of more than 5 per cent. Only in case of three chambers, however, the rate will reach 5 per cent when the average number of the patients per day is 0.481. 3. According to the results above, a hospital equipped with three hyperbaric chambers will be able to serve 166,485, 83,242, 55,495 and 41,620 of population, when the treatmet rate are 25, 50, 75 and 100 per cent. 4. The required number of hyperbaric chambers are estimated at 483, 963, 1,441 and 1,923 when the treatment rate are taken as 25, 50, 75 and 100 per cent. Therefore, the shortage are respectively turned out to be 312, 791. 1,270 and 1,752. The author believes that the methodology developed in this study will also be applicable to the problems of resource allocation for the other kinds of the emergency medical facilities.