• 한국인공지능학회지
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• 제4권1호
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• pp.11-13
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• 2016

These days, medical technology has been developed rapidly to meet desire of living healthy life. Average lifespan was extended to let people see a doctor because of many reasons. This study has shown rate of leaving of hospitals to investigate the rate of not only department of surgery but also department of internal medicine. Linear model, tree, classification rule, association and algorithm of data mining were used. This study investigated by using J48 and AD tree of decision-making tree In this study, J48 and AD tree of decision-making tree of data mining were used to investigate based on result of both data. Both algorithms were found to have similar performance. Both algorithms were not equivalent to require detailed experiment. Collect more experimental data in the future to apply from various points of view. Development of medical technology gives dream, hope and pleasure. The ones who suffer from incurable diseases need developed medical technology. Environment being similar to the reality shall be made to experiment exactly to investigate data carefully and to let the ones of various ages visit hospital and to increase survival rate.

• 대한산업공학회지
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• 제40권3호
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• pp.333-341
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• 2014

The purpose of this study is to forecast the penetration rate of renewable energy and a reasonable scale for the R&D investment plan in Korea based on the relationship between the diffusion and R&D investments drawn by analogy from empirical cases of advanced countries. Among numerous candidate developed countries, the German market was chosen based on the similarity of the diffusion patterns to those of the Korean plan. We then figured out how the investment triggers the growth of technology from the selected benchmark, and applied the technology S-curve relation formula to derive the desirable investment plan for Korea. The present paper is a pioneering attempt to forecast the diffusion process of renewable energy technology in Korea using the comparative analogy from cases of advanced countries.

• 국제학술발표논문집
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• The 1th International Conference on Construction Engineering and Project Management
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• pp.952-955
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• 2005

In the early 90's, we had serious shortage of construction engineers in Korea. The shortage was acute especially in construction quality control and supervision area, which were gaining social attention due to the road bridge and the department store collapse that took the hundreds of lives in the early 90's in Seoul, Korea. In order to meet the high demand of construction engineers, the engineering license regulations were changed in 1995. Engineers who did not pass the written exam but have equivalent working experience are given engineering license to practice engineering legally. Since year 2000, while the severe engineer-shortage has been resolved, the opposite situation has occurred: there is serious over-supply of construction engineers. Policy makers and engineering practitioners are agreed to bring back the old-fashioned written exam engineer licensing system like before 1995, i.e., no more written exam exemption. However, the engineers who obtained license without taking written exam may not want to go back to old policy which would take their license. It is required to provide appropriate grace period before the new policy takes effect to minimize the impact of the changes. This paper forecasts the supply-demand of construction engineers providing the basis for the most appropriate policy changes.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2021년도 춘계학술대회
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• pp.280-282
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• 2021

주관적 판단을 적용하여 예보되는 미세먼지 예보의 문제를 해결하기 위해 딥러닝 알고리즘을 이용하여 미세먼지 예측 모델을 설계하였다. 딥러닝 알고리즘 중 RNN과 LSTM을 이용하였으며, 하이퍼 파라미터 탐색을 통해 최적의 파라미터를 적용하여 설계하였다. RMSE와 예측 정확도를 통해 두 모델의 예측 성능을 평가하였다. 성능 평가 결과, RMSE와 전체 정확도에서 큰 차이는 없었으나 세부 예측 정확도의 차이가 있음을 확인하였다.

• 한국컴퓨터정보학회:학술대회논문집
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• 한국컴퓨터정보학회 2021년도 제63차 동계학술대회논문집 29권1호
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• pp.281-282
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• 2021

본 논문에서는 항공 수요예측을 위한 빅데이터 기반 플랫폼의 설계 및 실증 결과를 제시한다. 항공 수요예측 통합 플랫폼은 항공산업 관련 데이터를 Open API, RSS Feed, 웹크롤러(Web Crawler) 등을 이용하여 수집 및 분석하여 자체 개발한 항공 수요예측 알고리즘을 기반으로 결과를 시각화하여 보여주도록 구현되어 있다. 또한, 제안하는 플랫폼의 사용자 인터페이스를 통해 변수 설정을 하여 단위별(Global, National 등), 기간별(단기, 중장기 등), 유형별(여객, 화물 등) 예측 통계 자료를 도출할 수 있다. 플랫폼의 성능 검증을 위해 정형화된 데이터를 비롯하여 소셜네트워크서비스(SNS), 검색엔진 등에서 수집한 비정형 데이터까지 활용하여 특정 키워드의 빈도와 특정 노선에 대한 항공 수요간 상관관계를 분석하였다. 개발한 통합 플랫폼의 지능형 항공 수요예측 알고리즘을 통해 전반적인 공항 운영 및 공항 운영 정책 수립에 기여할 것으로 예상한다.

• 한국IT서비스학회지
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• 제19권4호
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• pp.49-61
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• 2020

Prior studies on technology predictions attempted to predict the emergence and spread of emerging technologies through the analysis of correlations and changes between data using objective data such as patents and research papers. Most of the previous studies predicted future technologies only from the viewpoint of technology development. Therefore, this study intends to conduct technical forecasting from the perspective of the consumer by using keyword search frequency of search portals such as NAVER before and after the introduction of emerging technologies. In this study, we analyzed healthcare technologies into three types : measurement technology, platform technology, and remote service technology. And for the keyword analysis on the healthcare, we converted the classification of technology perspective into the keyword classification of consumer perspective. (Blood pressure and blood sugar, healthcare diagnosis, appointment and prescription, and remote diagnosis and prescription) Naver Trend is used to analyze keyword trends from a consumer perspective. We also used the ARIMA model as a technology prediction model. Analyzing the search frequency (Naver trend) over 44 months, the final ARIMA models that can predict three types of healthcare technology keyword trends were estimated as "ARIMA (1,2,1) (1,0,0)", "ARIMA (0,1,0) (1,0,0)", "ARIMA (1,1,0) (0,0,0)". In addition, it was confirmed that the values predicted by the time series prediction model and the actual values for 44 months were moving in almost similar patterns in all intervals. Therefore, we can confirm that this time series prediction model for healthcare technology is very suitable.

• 한국융합학회논문지
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• 제8권3호
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• pp.15-22
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• 2017

최첨단 과학기술 시대를 맞아 사람들은 재난재해 예경보 시스템 및 재난재해 대응 시스템들이 잘 갖추어져 있다고 믿고 있으나 세월호 사건 등에서 알 수 있듯이 현실에서는 제대로 된 재난재해 예경보 및 대응 시스템이 갖추어져 있지 않은 상황이다. 기존의 재난재해 예경보 시스템의 경우 대부분 효율성이 낮은 센서 정보를 기반으로 하고 있으며, 영상 정보는 모니터링 요원에 의해 수동적으로 감시되고 있다. 또한 인식된 재난 재해에 대해서도 어떻게 대응하고 처리할 것인지에 대한 대응 시스템과의 연계가 미흡하다. 이에 따라 본 논문에서 CCTV 영상정보를 기반으로 특정 재난재해의 발생여부 및 정도를 최대한 빠르고 정확하게 인식하고 위기대응 매뉴얼에 근거하여 이를 모든 관련부처나 담당자들에게 자동으로 통보함으로써 효과적인 위기대응이 가능한 CCTV 기반 재난재해 인식 및 실시간 위기 대응 기술을 제안한다.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2002년도 ITC-CSCC -1
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• pp.262-264
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• 2002

The characteristic features of Malaysia's climate is has stable temperature, with high humidity and copious rainfall. Weather forecasting is an important task in Malaysia as it could affetcs man irrespective of mans job, lifestyle and activities especially in the agriculture. In Malaysia, numerical method is the common used method to forecast weather which involves a complex of mathematical computing. The models used in forecasting are supplied by other counties such as Europe and Japan. The goal of this project is to forecast weather using another technology known as artificial neural network. This system is capable to learn the pattern of rainfall in order to produce a precise forecasting result. The supervised learning technique is used in the loaming process.

• 기술혁신연구
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• 제13권1호
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• pp.1-24
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• 2005

This paper applies a prelaunch forecasting model to the Home-Networking (HN) market of South Korea. The HN market of Korea is categorized into two distinctive markets. One HN market consists of new apartments in which builders install HN and the other HN market consists of existing houses in which residents purchase HN Among these markets, this paper focuses on existing houses as capturing consumers' choice. To forecast sales of HN for existing houses, we use a conjoint model based on our survey data of consumer preferences. By incorporating various indicators of HN technologies into our conjoint model, we also forecast diffusion of HN system embodied in PLC or Wireless Lan. We call this model Choice-Based Diffusion Model. In addition, based on the simulation experiments, we also identify important factors that affect the demands of HN system.

• Ocean and Polar Research
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• 제36권4호
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• pp.505-514
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• 2014

The development of deep seabed manganese nodules has been carried out with the aim of commercial development in 2023. It is important to forecast the price of the four metals (copper, nickel, cobalt, and manganese) extracted from manganese nodules because price change is a criterion for investment decision. The main purpose of the study is to forecast the price of four metals using the ARIMA model and VAR model, and calculate the MAPE to compare a goodness-of-fit between the two models. The estimated results of the two models reveal statistical significance and are in keeping with economic theory. The results of MAPE for goodness-of-fit show that the VAR model is between 0.1 and 0.2, and the ARIMA model is between 0.4 and 0.6. That is, the VAR model is better than the ARIMA model in forecasting changes in the price of metals.