• 한국기후변화학회지
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• 제7권2호
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• pp.193-203
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• 2016

The importance of forecasting agricultural production is receiving attention while climate change is accelerating. This study suggested three types of crop yield forecasting model for major vegetable crops by using downscaled meteorological information of main production area on farmland level, which identified as limitation from previous studies. First, this study conducted correlation analysis with seven types of farm level downscaled meteorological informations and reported crop yield of main production area. After, we selected three types of meteorological factors which showed the highest relation with each crop species and regions. Parameters were deducted from meterological factor with high correlation but crop species number was neglected. After, crop yield of each crops was estimated by using the three suggested types of models. Chinese cabbage showed high accuracy in overall, while the accuracy of daikon and onion was quiet revised by neglecting the outlier. Chili and garlic showed differences by region, but Kyungbuk chili and Chungnam, Kyungsang garlic appeared significant accuracy. We also selected key meteorological factor of each crops which has the highest relation with crop yield. If the factor had significant relation with the quantity, it explains better about the variations of key meteorological factor. This study will contribute to establishing the methodology of future studies by estimating the crop yield of different species by using farmland meterological information and relatively simplify multiple linear regression models.

• 산업경영시스템학회지
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• 제33권4호
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• pp.167-177
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• 2010

Recent competitive and technological changes during the past decade have accelerated the need for better capital recovery methods. Competition and technology have together shortened the expected lives of property which could not have been forecasted several years ago. Since the usage of technological growth models has been prevalent in various technological forecasting environments, the various forms of growth models have become numerous. Of six such models studied, some models do significantly better than others, especially at low penetration levels in predicting future levels of growth. A set of criteria for choosing an appropriate model for technological growth models was developed. Two major characteristics of an S-shaped curve were elected which differentiate the various models; they are the skewness of the curve and underlying assumptions regarding the variance of error structure of the model.

• 한국공간정보시스템학회 논문지
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• 제7권1호
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• pp.3-11
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• 2005

본 과제는 정통부가 839 IT 신 성장 동력으로 추진 중인 텔레매틱스를 주 대상으로 한 무선공간정보서비스 기술 개발 사업을 성공적으로 수행하기 위해 필요한 최적의 인력을 예측하는 기법을 제시하고 2004년부터 2008년까지의 중기 인력 수요를 예측하는데 그 목적이 있다. 텔레매틱스 인력수요 예측을 위하여 한국의 현실에 적합한 인력 수요예측 모델을 제시하였다. 인력 수요 예측은 국내외 전문 기관들이 조사한 텔레매틱스 산업 추정치와 1인당 노동생산성을 감안하여 분야별 전체 인력수요 전망 구하였다. 또한 실태조사에서 도출된 분야별 직종별 취업구조 등을 적용하여 분야별 직종별 인력 수요를 도출한 후 이에 평균 탈락율을 감안하여 연도별 신규 인력 수요를 도출하였다.

• 한국대기환경학회지
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• 제26권6호
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• pp.666-682
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• 2010

The forecasting system for Today's and Tomorrow's PM10 was developed based on the statistical model and the forecasting was performed at 9 AM to predict Today's 24 hour average PM10 concentration and at 5 PM to predict Tomorrow's 24 hour average PM10. The Today's forecasting model was operated based on measured air quality and meteorological data while Tomorrow's model was run by monitored data as well as the meteorological data calculated from the weather forecasting model such as MM5 (Mesoscale Meteorological Model version 5). The observed air quality data at ambient air quality monitoring stations as well as measured and forecasted meteorological data were reviewed to find the relationship with target PM10 concentrations by the regression analysis. The PM concentration, wind speed, precipitation rate, mixing height and dew-point deficit temperature were major variables to determine the level of PM10 and the wind direction at 500 hpa height was also a good indicator to identify the influence of long-range transport from other countries. The neural network, regression model, and decision tree method were used as the forecasting models to predict the class of a comprehensive air quality index and the final forecasting index was determined by the most frequent index among the three model's predicted indexes. The accuracy, false alarm rate, and probability of detection in Tomorrow's model were 72.4%, 0.0%, and 42.9% while those in Today's model were 80.8%, 12.5%, and 77.8%, respectively. The statistical model had the limitation to predict the rapid changing PM10 concentration by long-range transport from the outside of Korea and in this case the chemical transport model would be an alternative method.

• 중소기업융합학회논문지
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• 제6권4호
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• pp.93-98
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• 2016

최근 스마트 그리드와 관련된 프로젝트가 선진국을 중심으로 활발하게 연구되고 있다. 특히, 전력 문제의 장기적 안정 대책으로 분산전원이 주목받고 있다. 본 논문에서는 분산형 전원의 출력 예측을 위해서 물리모델과 통계모델을 조합하여 예측 정보 오차율을 비교분석할 수 있는 3차원 기상 수치 모델을 제안한다. 제안 모델은 분산형 전원의 예측정보를 향상시킬 수 있어 안정적인 전력계통 연계를 위한 예측시스템을 가능하다. 성능평가 결과, 제안모델은 발전량 예측 정확도가 4.6% 개선되었고, 온도보정 예측 정확도는 3.5% 향상되었다. 마지막으로 일사량 보정 정확도는 1.1% 향상되었다.

• 한국수산과학회지
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• 제26권4호
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• pp.363-368
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• 1993

어획량의 단기 예측은 자원관리에 있어 중요한 항목이지만 전통적인 개체군 모델은 수산자원 관리에 있어 실제적으로 요구되는 예측력이 크게 부족하다. 다종 또는 생태계 모델도 요구되는 매개변수의 수가 많아 실제적 적용이 어렵다. 반면에 단변수 시계열 분석법은 시계열 자체에서 변동성에 관한 특성을 추정하여 이를 토대로 장래 변동성을 예측함으로 최소한의 자료를 가지고 비교적 정확한 단기예측이 가능하므로 유용성이 높다. 본 연구에서는 ARIMA 시계열 모델을 $1971{\sim}1988$년 간의 한국근해의 월별 갈치어획량 자료에 적용하였다. 여기서 나온 예측치와 분석에 포함되지 않았던 $1989{\sim}1990$년 간의 어획량과 비교하였다. 분석 결과 예측치와 실제어획량이 잘 일치하였으며(r=0.938) 평균상대오차는 $59.5\%$였다.

• 한국항만경제학회지
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• 제29권1호
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• pp.67-76
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• 2013

해운경기와 밀접한 관계를 갖는 세계 경기가 유럽재정위기와 같은 일련의 사건으로 침체국면에서 벗어나지 못하고 있어 장기적인 해운시황에 대한 우려가 커지고 있으며, BDI 건화물선 종합운임지수가 1000포인트에도 도달하지 못해 해운기업의 어려움을 가중시키고 있다. 본고는 해운경기의 불황탈피가 2013년에 가능한가를 파악하기 위해 BDI를 예측하는데 목적을 둔다. 해상운임에 영향을 미치는 변수들로 구성된 다변량모형 대신 BDI로만 구성된 단일변량모형인 자기회귀-이동평균모형과 장기순환과정을 보여주는 Hodrick-Prescott 필터 기법을 이용하여 2013년의 BDI를 예측한다. 3개의 ARIMA모형과 2개의 개입-ARIMA 모형을 이용하여 2013년에도 지속적으로 BDI가 하락하는 760과 670사이에서 움직인다는 것을 보인다. HP기법을 통한 예측은 750에서 556사이의 변동을 예상하여 ARIMA모형보다 해운경기를 더 비관적이라는 것도 밝힌다. 또한 5개의 ARIMA모형의 예측오류가 RW모형보다 낮을 뿐만 아니라 그 크기가 대단히 작아 예측치가 크게 빗나갈 가능성이 낮다는 것도 보인다.

• 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.

• 한국환경과학회지
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• 제15권2호
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• pp.141-155
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• 2006

This study is aimed at the development of a runoff forecasting model to solve the uncertainties occurring in the process of rainfall-runoff modeling and improve the modeling accuracy of the stream runoff forecasting, The study area is the downstream of Naeseung-chun. Therefore, time-dependent data was obtained from the Wolpo water level gauging station. 11 and 2 out of total 13 flood events were selected for the training and testing set of model. The model performance was improved as the measuring time interval$(T_m)$ was smaller than the sampling time interval$(T_s)$. The Neuro-Fuzzy(NF) and TANK models can give more accurate runoff forecasts up to 4 hours ahead than the Feed Forward Multilayer Neural Network(FFNN) model in standard above the Determination coefficient$(R^2)$ 0.7.

• 경영과학
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• 제19권2호
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• pp.125-137
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• 2002

The telecommunications market is expanding rapidly and becoming more substitutive. In this environment, demand forecasting is very difficult, yet important for both practitioners and researchers. in this paper, we adopt the modeling approach proposed dy Jun and Park ［6］. The basic premise is that demand patterns result from choice behavior, where customers choose a product to maximize their utility. We apply a choice-based substitutive diffusion model to the Korean mobile telecommunication service market where digital service has completely replaced analog service. In comparison with Bass-type multigeneration models. our model provides superior fitting and forecasting performance. The choice-based model is useful in that it enables the description of such complicated environments and provides the flexibility to include marketing mix variables such as price and advertising in the regression analysis.