• 전기학회논문지
• /
• 제65권5호
• /
• pp.851-856
• /
• 2016

Wind speed is heavily fluctuated and quite local than other weather elements. It is difficult to improve the accuracy of prediction only in a numerical prediction model. An MOS (Model Output Statistics) technique is used to correct the systematic errors of the model using a statistical data analysis. The Most of previous MOS has used a linear regression model for weather prediction, but it is hard to manage an irregular nature of prediction of wind speed. In order to solve the problem, a nonlinear regression method using SVR (Support Vector Regression) is introduced for a development of MOS for wind speed prediction. Experiments are performed for KLAPS (Korea Local Analysis and Prediction System) re-analysis data from 2007 to 2013 year for Jeju Island and Busan area in South Korea. The MLR and SVR based linear and nonlinear methods are compared to each other for prediction accuracy of wind speed. Also, the comparison experiments are executed for the variation in the number of UM elements.

• 한국항공운항학회지
• /
• 제23권3호
• /
• pp.28-34
• /
• 2015

An analysis method of trajectory prediction has been suggested and the developed trajectory prediction module, which is an important functional component of the Arrival Manager (AMAN) of Jeju airport, has been tested by applying the suggested method. The objective of this method is to improve prediction performance of the trajectory prediction module. The trajectory prediction module predicts the trajectories based on the real-time track data and flight plans. Therefore, the suggested analysis method includes the simulation framework which is based on real-time playback, recording, and graphic display systems for testing. Besides, the definition of time error, which is a important index for the time based scheduling system, such as AMAN, is included in the suggested analysis method. An example of arrival time prediction accuracy improvement through the suggested analysis method has also been presented.

• 융합신호처리학회논문지
• /
• 제7권2호
• /
• pp.53-59
• /
• 2006

동적 신경망은 시스템 식별과 신호예측과 같이 temporal 신호처리가 요구되는 여러 분야에서 적용되어 왔다. 본 논문에서는 신경망의 동특성을 향상시키기 위해 순방향 다층 신경망의 히든 층에 감마(Gamma) 메모리 커넬을 사용하는 감마 신경망(GAM)을 제안하고, 적응필터로 제안된 신경망을 사용하여 비선형 적응예측을 다루고 있다. 제안된 신경망은 비선형 신호예측을 통해 평가되었으며, 예측성능의 상대적인 비교를 위해 순방향 신경망(FNN)과 리커런트 신경망(RNN)과 비교하였다. 시뮬레이션 결과에 의하면 GAM 신경망은 수렴속도와 예측의 정확도에서 이러한 신경망보다 더 우수한 동작을 수행함으로써, 제안된 신경망이 기존의 다층 신경망보다 비정적 신호에 대한 비선형 예측에 더 효과적인 예측모델임을 확인하였다.

• 한국멀티미디어학회논문지
• /
• 제19권8호
• /
• pp.1530-1537
• /
• 2016

Recently, solar power generation shows the significant growth in the renewable energy field. Using the short-term prediction, it is possible to control the electric power demand and the power generation plan of the auxiliary device. However, a short-term prediction can be used when you know the weather forecast. If it is not possible to use the weather forecast information because of disconnection of network at the island and the mountains or for security reasons, the accuracy of prediction is not good. Therefore, in this paper, we proposed a system capable of short-term prediction of solar power generation amount by using only the weather information that has been collected by oneself. We used temperature, humidity and insolation as weather information. We have applied a moving average to each information because they had a characteristic of time series. It was composed of min, max and average of each information, differences of mutual information and gradient of it. An artificial neural network, SVM and RBF Network model was used for the prediction algorithm and they were combined by Ensemble method. The results of this suggest that using a moving average during pre-processing and ensemble prediction models will maximize prediction accuracy.

• 대한안전경영과학회지
• /
• 제26권1호
• /
• pp.39-44
• /
• 2024

In order to prevent accidents via defective ammunition, this paper analyzes recent research on ammunition life prediction methodology. This workanalyzes current shelf-life prediction approaches by comparing the pros and cons of physical modeling, accelerated testing, and statistical analysis-based prediction techniques. Physical modeling-based prediction demonstrates its usefulness in understanding the physical properties and interactions of ammunition. Accelerated testing-based prediction is useful in quickly verifying the reliability and safety of ammunition. Additionally, statistical analysis-based prediction is emphasized for its ability to make decisions based on data. This paper aims to contribute to the early detection of defective ammunition by analyzing ammunition life prediction methodology hereby reducing defective ammunition accidents. In order to prepare not only Korean domestic war situation but also the international affairs from Eastern Europe and Mid East countries, it is very important to enhance the stability of organizations using ammunition and reduce costs of potential accidents.

• 한국병원경영학회지
• /
• 제11권3호
• /
• pp.19-41
• /
• 2006

The Objective of this study was to design the model which predict the future cash flow of hospitals and on the basis of designed model to support sound hospital management by the prediction of future cash flow. The five cash flow measurement variables discussed in financial accrual part were used as variables and these variables were defined as NI, NIDPR, CFO, CFAI, CC. To measure the cash flow B/S related variables, P/L related variables and financial ratio related variables were utilized in this study. To measure cash flow models were designed and to estimate the prediction ability of five cash flow models, the martingale model and the market model were utilized. To estimate relative prediction outcome of cash flow prediction model and simple market model, MAE and MER were used to compare and analyze relative prediction ability of the cash flow model and the market model and to prove superiority of the model of the cash flow prediction model, 32 Regional Public Hospital's cross-section data and 4 year time series data were combined and pooled cross-sectional time series regression model was used for GLS-analysis. To analyze this data, Firstly, each cash flow prediction model, martingale model and market model were made and MAE and MER were estimated. Secondly difference-test was conducted to find the difference between MAE and MER of cash flow prediction model. Thirdly after ranking by size the prediction of cash flow model, martingale model and market model, Friedman-test was evaluated to find prediction ability. The results of this study were as follows: when t-test was conducted to find prediction ability among each model, the error of prediction of cash flow model was smaller than that of martingale and market model, and the difference of prediction error cash flow was significant, so cash flow model was analyzed as excellent compare with other models. This research results can be considered conductive in that present the suitable prediction model of future cash flow to the hospital. This research can provide valuable information in policy-making of hospital's policy decision. This research provide effects as follows; (1) the research is useful to estimate the benefit of hospital, solvency and capital supply ability for substitution of fixed equipment. (2) the research is useful to estimate hospital's liqudity, solvency and financial ability. (3) the research is useful to estimate evaluation ability in hospital management. Furthermore, the research should be continued by sampling all hospitals and constructed advanced cash flow model in dimension, established type and continued by studying unified model which is related each cash flow model.

• 방송공학회논문지
• /
• 제17권5호
• /
• pp.781-788
• /
• 2012

HEVC에서는 움직임 예측 시, 복잡도를 줄이기 위해 고속 탐색 기법이 사용된다. 고속 탐색 기법에는 SAD 계산 복잡도를 줄인 부-화소 단위 SAD 계산 기법(sub-sampled SAD)과 양-예측시의 단-예측 반복횟수를 줄인 간소화된 양-예측 기법으로 이루어져 있다. 고속 탐색 기법으로 인해 복잡도는 크게 줄었지만 부호화 이득 역시 감소하였다. 본 논문에서는 감소된 부호화 효율을 보상하기 위해 간소화된 양-예측을 확장하였고 확장된 양-예측으로 증가된 복잡도를 줄이기 위해 예측 비용 기반의 복잡도 감소 기법들을 제안한다. 예측 비용 기반의 복잡도 감소 기법은 양-예측 조기 종료 기법과 양-예측 생략 기법으로 이루어져 있다. HM 6.0 참조 소프트웨어와 비교하여 확장된 양-예측 기법과 예측 비용 기반의 복잡도 감소 기법으로 복잡도의 증가 없이 평균 0.42%의 BD-bitrate을 감소시켰다.

• 산경연구논집
• /
• 제8권4호
• /
• pp.47-52
• /
• 2017

Purpose - This current study will investigate the average financial ratio of top and failed five-star hotels in the Jeju area. A total of 14 financial ratio variables are utilized. This study aims to; first, assess financial ratio of the first-class hotels in Jeju to establishing variables, second, develop distress prediction model for the first-class hotels in Jeju district by using logit analysis and third, evaluate distress prediction capacity for the first-class hotels in Jeju district by using logit analysis. Research design, data, and methodology - The sample was collected from year 2015 and 14 financial ratios of 12 first-class hotels in Jeju district. The results from the samples were analyzed by t-test, and the independent variables were chosen. This was an empirical study where the distress prediction model was evaluated by logit analysis. This current research has focused on critically analyzing and differentiating between the top and failed hotels in the Jeju area by utilizing the 14 financial ratio variables. Results - The verification result of the accuracy estimated by logit analysis has shown to indicate that the distress prediction model's distress prediction capacity was 83.3%. In order to extract the factors that differentiated the top hotels in the Jeju area from the failed hotels among the 14 chosen, the analysis of t-black was utilized by independent variables. Logit analysis was also used in this study. As a result, it was observed that 5 variables were statistically significant and are included in the logit analysis for discernment of top and failed hotels in the Jeju area. Conclusions - The distress prediction press' prediction capability was compared in this research analysis. The distress prediction press prediction capability was shown to range from 75-85% by logit analysis from a previous study. In this current research, the study's prediction capacity was shown to be 83.33%. It was considered a high number and was found to belong to the range of the previous study's prediction capacity range. From a practical perspective, the capacity of the assessment of the distress prediction model in the top and failed hotels in the Jeju area was considered to be a prominent factor in applications of future hotel appraisal.

• 대한토목학회논문집
• /
• 제32권6D호
• /
• pp.599-605
• /
• 2012

교통개방시점의 예측은 공사 계획을 위해 중요하며 이를 위해 에폭시 아스팔트 혼합물의 양생에 따른 강도를 예측하는 것이 필요하다. 본 연구에서는 에폭시 아스팔트 혼합물의 양생온도와 시간에 따른 마샬안정도를 측정하고 이를 이용해 강도 발현식을 구하였으며, 변화하는 온도와 강도에 따른 반응속도를 반영할 수 있도록 화학적 반응속도론을 이용하여 에폭시 아스팔트 강도 예측모델을 개발하였다. 예측모델을 사용하여 에폭시 아스팔트 포장이 적용된 국내 교량에 대해 교통개방시기를 예측하였다. 2009년~2011년의 기상조건에 따라 가정된 포장체 온도를 사용한 예측결과는 실제 교통개방일과 17일의 차이가 발생했으나 이는 2012년의 실제 기상상태와의 차이 때문이다. 실제 측정된 포장 온도를 예측모델에 대입할 경우 2일의 교통개방가능일 차이가 있었으며, 상관관계 분석 결과 R2가 0.95로 실제 강도값과 매우 유사한 결과를 얻을 수 있었다. 기상상태와 포장체의 온도에 대한 충분한 데이터를 확보한다면 에폭시 아스팔트 강도 예측모델을 사용하여 상당히 신뢰도 있는 교통개방 가능 시기의 예측이 가능한 것으로 나타났다.

• 한국정보과학회논문지:정보통신
• /
• 제34권3호
• /
• pp.156-167
• /
• 2007

본 논문에서는 VBR(Variable-Bit-Rate) 트래픽의 비선형적이고 버스티한 특성을 모델화 한 GOP ARIMA(ARIMA for Group Of Pictures) 모델을 칼만 필터 알고리즘을 이용하여 실시간으로 예측하는 기법을 제안한다. 칼만 필터를 이용한 예측 기법은 GOP ARIMA의 상태공간 모델링 과정과 향후 N초 간의 트래픽을 예측하는 과정으로 구성된다. 실험을 위해 GOP의 크기가 각각 15인 세 가지 종류의 MPEG VBR 트래픽(뉴스, 드라마, 스포츠)을 제작하였고, 칼만 필터를 이용한 세 가지 종류의 트래픽의 예측 결과를 선형 예측법과 이중 지수 평활법을 이용해 예측한 결과와 비교해 예측 성능이 상대적으로 우수함을 확인할 수 있었다. 또한 예측값에 신뢰 구간을 설정하는 신뢰 구간 분석법을 통해 트래픽 관점에서 장면 변화를 예측하는 방법을 제시하였다. 본 논문의 칼만 필터 기반의 예측 알고리즘은 MPEG 기반 VBR 트래픽을 비롯한 기타 인터넷 트래픽을 실시간으로 예측하는 방법과 이를 이용해 인터넷 서버의 설계 및 자원 할당 정책 등을 위한 트래픽 엔지니어링 연구에 기여할 수 있을 것이다.