• Current Optics and Photonics
• /
• 제4권3호
• /
• pp.174-185
• /
• 2020

Multiscattering occurs when a laser transmits into dense atmosphere targets (e.g. fogs, smoke or clouds), which can cause depolarization effects even though the scattering particles are spherical. In addition, multiscattering effects have additional information about microphysical properties of scatterers. Thus, multiscattering can be utilized to study the microphysical properties of the liquid water cloud. In this paper, a Monte Carlo method was used to simulate multi-scattering transmission properties of Lidar signals in the cloud. The results showed the slope of the degree of linear polarization (SLDLP) can be used to invert the extinction coefficient, and then the cloud effective size (CES) and the liquid water content (LWC) may be easily obtained by using the extinction coefficient and saturation of the degree of linear polarization (SADLP). Based on calculation results, a microphysical properties inversion method for a liquid cloud was presented. An innovative multiscattering polarization Lidar (MSPL) system was constructed to measure the LWC and CES of the liquid cloud, and a new method based on the polarization splitting ratio of the Polarization Beam Splitter (PBS) was developed to calibrate the polarization channels of MSPL. By analyzing the typical observation data of MSPL observation in the northern suburbs of Nanjing, China, the LWC and CES of the liquid water cloud were obtained. Comparisons between the results from the MSPL, MODIS and the Microwave radar data showed that, the microphysical properties of liquid cloud could be retrieved by combining our MSPL and the inversion method.

• 한국지반공학회:학술대회논문집
• /
• 한국지반공학회 2005년도 춘계 학술발표회 논문집
• /
• pp.825-830
• /
• 2005

Cut slope and facility of management investigation is the protection of humans and properties. it is very important the prevention of disaster facility and the damage of the slope protection facility. It is very difficult to forecast slope stability, disaster possibility and collapse. It will be able to minimize the damage which it prepare against slope facility and cut slope of deformable investigation and collapse and the disaster. therefore those deformable investigation is important. Investigations execute upheaval, crack, sliding for slope and cut slope reinforcement. Investigation executes forecast in place where the construction problem, the effect which the damage in road traffic or the contiguity facility.

• Journal of Electrical Engineering and Technology
• /
• 제13권2호
• /
• pp.591-598
• /
• 2018

Short term load forecasts complexly affected by socioeconomic factors and weather variables have non-linear characteristics. Thus far, researchers have improved load forecast technologies through diverse techniques such as artificial neural networks, fuzzy theories, and statistical methods in order to enhance the accuracy of load forecasts. Short term load forecast errors for special days are relatively much higher than that of weekdays. The errors are mainly caused by the irregularity of social activities and insufficient similar past data required for constructing load forecast models. In this study, the load characteristics of Lunar New Year's Day holidays well known for the highest error occurrence holiday period are analyzed to propose a load forecast technique for Lunar New Year's Day holidays. To solve the insufficient input data problem, the similarity of the load patterns of past Lunar New Year's Day holidays having similar patterns was judged by Euclid distance. Lunar New Year's Day holidays periods for 2011-2012 were forecasted by the proposed method which shows that the proposed algorithm yields better results than the comprehensive analysis method or the knowledge-based method.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 2005년도 ICCAS
• /
• pp.271-274
• /
• 2005

Under competitive power markets, various long-term and short-term contracts based on spot price are used by producers and consumers. So an accurate forecasting for spot price allow market participants to develop bidding strategies in order to maximize their benefit. Artificial Neural Network is a powerful method in forecasting problem. In this paper we used Radial Basis Function(RBF) network to forecast spot price. To learn ANN, in addition to price history, we used some other effective inputs such as load level, fuel price, generation and transmission facilities situation. Results indicate that this forecasting method is accurate and useful.

• Nuclear Engineering and Technology
• /
• 제52권6호
• /
• pp.1334-1339
• /
• 2020

This paper presents an empirical and comprehensive forecasting analysis of the uranium price. Prices are generally difficult to forecast, and the uranium price is not an exception because it is affected by many external factors, apart from imbalances between demand and supply. Therefore, a systematic analysis of multiple forecasting methods and combinations of them along repeated forecast origins is a way of discerning which method is most suitable. Results suggest that i) some sophisticated methods do not improve upon the Naïve's (horizontal) forecast and ii) Unobserved Components methods are the most powerful, although the gain in accuracy is not big. These two facts together imply that uranium prices are undoubtedly subject to many uncertainties.

• 한국산림과학회지
• /
• 제99권2호
• /
• pp.197-203
• /
• 2010

The data of average temperature, average relative humidity, precipitation and average wind speed were collected from 674 meteorological stations in China. A specific procedure that processes original data into a new data format needed in forest fire danger rating forecast system of China was introduced systematically, and the feasibility of this method was validated in this paper. In addition, a set of meteorological data processing software was constructed by the secondary development of GIS in order to realize automation of processing data for the system. Results showed that the approach preformed well in handling temperature, average relative humidity and average wind speed, and the processing effect of precipitation was acceptable. Moreover, the automated procedure could be achieved by GIS and the working efficiency was about 3 times as much as that of manual handling. The informationization level of processing meteorological data was greatly enhanced.

• 산업경영시스템학회지
• /
• 제22권51호
• /
• pp.1-10
• /
• 1999

In recent industry society, it is revealed that, as an increase in the use of automated manufacturing and process inspection technology, the data from mass production system exhibits some degrees of autocorrelation. The operation characteristics of traditional control charts developed under the independence assumption are adversely affected by the presence of serial correlation. Therefore, when autocorrelated construction contacted with time-series models explain, the time-series models are the Box-Jenkins forecast models which have been proposed as the best forecasting tool which allows for partitioning of variation into result from the autocorrelation structure and variation due to unusual but assignable causes. In this paper, for the AR(1) process of Box-Jenkins forecast models, when the constant term ξ are zero and different from zero, I want to analyze the sensitivity of (equation omitted), CUSUM and EWMA control chart for forecast residuals.

• 산업공학
• /
• 제14권1호
• /
• pp.54-58
• /
• 2001

In this study, we suggest a multi-generation Lotka-Volterra model, which is a competition model using game theory and complex system theory. The suggested model shows many improvements to weakness of a well known Bass model to forecast new technology in competitive markets. We show that the Lotka-Volterra model has strong power to forecast mobile communication services when it is used for competition of 1st generation mobile phone service and 2nd generation phone service in Korea. We finally use the model to forecast IMT-2000 service, the 3rd generation mobile communication service.

• 한국항해항만학회:학술대회논문집
• /
• 한국항해항만학회 2005년도 춘계학술대회 논문집
• /
• pp.479-485
• /
• 2005

최근 RFID 기술의 급속한 확산은 기존 인식매체의 한계를 극복하고, 기업 및 산업 전반에 새로운 혁신을 가져올 것으로 예상된다. 특히 항만물류산업의 경우 RFID 기술이 적용될 경우 많은 파급효과를 가져올 것으로 예상된다. 우리나라에서는 정부의 각종 시범사업을 통해 RFID 기술을 항만물류산업에 도입하고 있으나 현실적인 개선과제 및 기술도입 전략 등에 대한 연구 부족 등으로 많은 어려움을 겪고 있다. 본 연구에서는 기존 문헌 조사와 현업 설문 분석을 통해 단위 업무별 RFID 기술도입을 위한 우선순위를 선정하여 기술도입을 위한 로드맵을 제시하고자 한다. 향후 본 연구는 항만물류산업의 RFID 기술도입에 성공적인 가이드라인이 될 것이라 기대된다.

• Journal of Ecology and Environment
• /
• 제44권2호
• /
• pp.98-105
• /
• 2020

Background: The purpose of this study, mosquito forecast system implemented by Seoul Metropolitan city, was to obtain the mosquito prediction formula by using the mosquito population data and the environmental data of the past. Results: For this study, the mosquito population data from April 1, 2015, to October 31, 2017, were collected. The mosquito population data were collected from the 50 smart mosquito traps (DMSs), two of which were installed in each district (Korean, gu) in Seoul Metropolitan city since 2015. Environmental factors were collected from the Automatic Weather System (AWS) by the Korea Meteorological Administration. The data of the nearest AWS devices from each DMS were used for the prediction formula analysis. We found out that the environmental factors affecting the mosquito population in Seoul Metropolitan city were the mean temperature and rainfall. We predicted the following equations by the generalized linear model analysis: ln(Mosquito population) = 2.519 + 0.08 × mean temperature + 0.001 × rainfall. Conclusions: We expect that the mosquito forecast system would be used for predicting the mosquito population and to prevent the spread of disease through mosquitoes.