• Korean Journal of Construction Engineering and Management
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• v.14 no.4
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• pp.24-34
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• 2013

Since 2004, the government decided to gradually introduce Actual Cost Data into cost estimate for improving problems of below-cost tendering and to reflect fair market price through competition and carry contract efficiently. However, there are many concerns that Actual Cost Data has not reflected real market price, even that has contributed to reduce the government's budget. General construction firm's burden for labor cost is imputed to specialty contractors and eventually it becomes construction worker's burden. Therefore, realization of Actual Cost Data is very important factor to settle this system. To understand realization level and make short term forecast, this paper drew construction group of which labor cost constitutes more than 95% of direct cost, and compares their Actual Cost Data with relevant skilled workers's unit wage and predicts using time series analysis. The bid price which is not be reflected market price accelerates work environment changes and leads to directly affect such as late disbursement of wages, bankruptcy to workers. Therefore this paper is expected to be used to the preliminary data for solving the problem and establishing improvement of Actual Cost Data.

• Journal of Internet of Things and Convergence
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• v.9 no.6
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• pp.57-62
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• 2023

This research is a comparative analysis of the U.S. S&P 500 index using the volatility breakout strategy against the Buy and Hold approach. The volatility breakout strategy is a trading method that exploits price movements after periods of relative market stability or concentration. Specifically, it is observed that large price movements tend to occur more frequently after periods of low volatility. When a stock moves within a narrow price range for a while and then suddenly rises or falls, it is expected to continue moving in that direction. To capitalize on these movements, traders adopt the volatility breakout strategy. The 'k' value is used as a multiplier applied to a measure of recent market volatility. One method of measuring volatility is the Average True Range (ATR), which represents the difference between the highest and lowest prices of recent trading days. The 'k' value plays a crucial role for traders in setting their trade threshold. This study calculated the 'k' value at a general level and compared its returns with the Buy and Hold strategy, finding that algorithmic trading using the volatility breakout strategy achieved slightly higher returns. In the future, we plan to present simulation results for maximizing returns by determining the optimal 'k' value for automated trading of the S&P 500 index using artificial intelligence deep learning techniques.

• Journal of the Korea Society of Computer and Information
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• v.16 no.2
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• pp.225-233
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• 2011

Stock market prices, economic indices, trends and changes of social phenomena, etc. are categorized as time series data. Research on time series data has been prevalent for a while as it could not only lead to valuable representation of data but also provide future trends as well as changes in direction. We take a conventional model based approach, known as Markov chain modeling for the prediction on stock market prices. To improve prediction accuracy, we apply Markov modeling over carefully selected intervals of training data to fit the trend under consideration to the model. Another method we take is to apply clustering to data and build models of the resultant clusters. We confirmed that clustered models are better off in predicting, however, with the loss of prediction rate.

• International Area Studies Review
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• v.14 no.2
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• pp.25-40
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• 2010

Accurate forecasting of volatility is of considerable interest in financial volatility research, particularly in regard to portfolio allocation, option pricing and risk management because volatility is equal to market risk. So, we attempted to delineate a model with good ability to forecast and identified stylized features of volatility, with a focus on volatility persistence or long memory in the Australian futures market. In this context, we assessed the long-memory property in the volatility of index futures contracts using three conditional volatility models, namely the GARCH, IGARCH and FIGARCH models. We found that the FIGARCH model better captures the long-memory property than do the GARCH and IGARCH models. Additionally, we found that the FIGARCH model provides superior performance in one-day-ahead volatility forecasts. As discussed in this paper, the FIGARCH model should prove a useful technique in forecasting the long-memory volatility in the Australian index futures market.

• Journal of the Korea Society of Computer and Information
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• v.28 no.7
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• pp.29-37
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• 2023

Due to climate change, interest in crop production and distribution is increasing, and attempts are being made to use bigdata and AI to predict production volume and control shipments and distribution stages. Prediction of agricultural product imports not only affects prices, but also controls shipments of farms and distributions of distribution companies, so it is important information for establishing marketing strategies. In this paper, we create an artificial intelligence prediction model that predicts the future import volume based on the wholesale market melon import volume data disclosed by the agricultural statistics information system and evaluate its accuracy. We create prediction models using three models: the Neural Prophet technique, the Ensembled Neural Prophet model, and the GRU model. As a result of evaluating the performance of the model by comparing two major indicators, MAE and RMSE, the Ensembled Neural Prophet model predicted the most accurately, and the GRU model also showed similar performance to the ensemble model. The model developed in this study is published on the web and used in the field for 1 year and 6 months, and is used to predict melon production in the near future and to establish marketing and distribution strategies.

• Monthly Korean Chicken
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• v.2 no.11 s.17
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• pp.2-8
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• 1996

배합사료 부가세 전면 영세율 적용방침 - 식품위해요소 중점 관리제도 - '식중독유발 닭고기 살모넬라는 극히 일부' - `97년 닭 MMA 물량 입찰 - 계열농가 입식물량 $20{\%}$ 감축키로 - 미국 옥수수 등 사료곡물 생산량 풍작 - 국내 닭고기 생산비 미국의 2배 - 닭고기 소비행태 조사보고서 발간 - 주한 외교대사관 부인 초청 `96국제 닭고기요리 경연대회 개최 - 육계업계, 수매비축자금지원 절실 - `97년 미국 가금육산업 낮은 성장률 예측 브라질, 사료가격 폭등 계열농가는 증가추세 - 영, MOYPARK사 미국 OSI에 팔려 - 닭고기 소비촉진홍보사업 활발히 전개 - 계열주체와 계약조건 개선 희망 - 수입축산물 불합격 증가 - 육계실용계 병아리 16만수 폐기처분 - 러시아 농업지원 강화

• ETRI Journal
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• v.10 no.1
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• pp.39-52
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• 1988

This study suggests the diffusion models to predict the spread pattern of telecommunications services. The extended models containing both (either) price and (or) income varible are offered on the basis of Bass model. At the empirical test using Korean telephone data, the models with either price or income varible are the best forecasting model under apriori selected econometric criteria.

• Proceedings of the KIEE Conference
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• 2008.11a
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• pp.83-85
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• 2008

The authors develop and compare the performance of short-term forecasting models on electricity market prices in Korea. The models are based on time-series methods. The outcome shows that the EGARCH model has the best results in the out-of-sample forecasts.

• Transactions of the Korean Society of Mechanical Engineers
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• v.13 no.6
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• pp.1339-1345
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• 1989

본 연구에서는 앞에서 개발된 온도 제어 시스템을 더욱 소형 경량화하기 위해 서 일반 마이크로 컴퓨터 대신에 원보드 마이컴(one-board micom)을 사용하였다. 원보드 마이컴은 프로그램을 기계어로 작성해야하는 어려움이 있으나 가격이 저렴하고 주변장치가 필요없으며, 크기가 작아 제어시스템을 소형경량화 시킬수 있는 장점이 있다.

• Proceedings of the Optical Society of Korea Conference
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• 2000.02a
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• pp.262-263
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• 2000

이온교환방법은 착색된 유리를 생산하기 위하여 수세기 전부터 연구되어 왔다. 1972년 Izawa와 Nagome가 silicate 유리에 Tl$^{+}$이온을 치환하여 평판 도파로를 만든 후, 이온교환은 도파로나 마이크로 렌즈제작 등에 활발하게 연구되어 왔다. 유리 도파로는 광의 진행손실이 적으며, 광섬유와의 우수한 호환성, 그리고, 제작이 용이하고 가격이 싼 장점 등으로 인하여 많은 연구가 진행되고 있는 재료이다. 그러나, 유리에 이온교환으로 광소자를 만들기 위해서는 굴절률변화를 정확하게 예측해야한다. 따라서, 유리에서 이온들의 확산특성을 정확하게 분석하고 실험적으로 확립하는 연구는 매우 중요하다고 하겠다. (중략)