• Journal of Environmental Impact Assessment
• /
• v.12 no.4
• /
• pp.245-257
• /
• 2003

$SO_2$ concentrations in the Seoul Metropolitan Area (SMA) were predicted by the regional segment ISCST3 modeling. The SMA was segmented by three modeling regions where the weather monitoring station exists since the area of the SMA, approximately $100km{\times}100km$, is too wide to be modeled by one modeling domain. The predicted concentrations by the model were compared with the measured concentrations at 39 air monitoring stations located in the SMA to validate the ISCST3 modeling coupled with the regional segment approach. The predicted concentrations by the regional segment method showed better performance in depicting the measurements than those by the non-segment ISCST3 modeling. The correction methods of the calculated concentrations reviewed were here the correlation method by the first order linear equation and the ratio method of observed to calculated concentrations. The corrected concentrations by two methods showed good agreement with the measured data. The ratio method was, however, easily applicable to the concentration correction in case of a wide modeling region considered in this study.

• Atmosphere
• /
• v.18 no.3
• /
• pp.237-248
• /
• 2008

A thermal index which considers metabolic heat generation of human body is proposed for operational forecasting. The new thermal index, Perceived Temperature (PT), is forecasted using Weather Research and Forecasting (WRF) mesoscale model and validated. Forecasted PT shows the characteristics of diurnal variation and topographic and latitudinal effect. Statistical skill scores such as correlation, bias, and RMSE are employed for objective verification of PT and input meteorological variables which are used for calculating PT. Verification result indicates that the accuracy of air temperature and wind forecast is higher in the initial forecast time, while relative humidity is improved as the forecast time increases. The forecasted PT during 2007 summer is lower than PT calculated by observation data. The predicted PT has a minimum Root-Mean-Square-Error (RMSE) of $7-8^{\circ}C$ at 9-18 hour forecast. Spatial distribution of PT shows that it is overestimated in western region, while PT in middle-eastern region is underestimated due to strong wind and low temperature forecast. Underestimation of wind speed and overestimation of relative humidity have caused higher PT than observation in southern region. The predicted PT from the mesoscale model gives appropriate information as a thermal index forecast. This study suggests that forecasted PT is applicable to the prediction of health warning based on the relationship between PT and mortality.

• Ocean Systems Engineering
• /
• v.6 no.2
• /
• pp.143-159
• /
• 2016

Cargo, such as a Tension Leg Platform (TLP), Semi-submersible platform (Semi), Spar or a circular Floating Production Storage and Offloading (FPSO), are frequently dry-transported on a Heavy Lift Vessel (HLV) from the point of construction to the point of installation. The voyage can span months and the overhanging portions of the hull can be subject to frequent wave slamming events in rough weather. Tie-downs or sea-fastening are usually provided to ensure the safety of the cargo during the voyage and to keep the extreme responses of the cargo, primarily for the installed equipment and facilities, within the design limits. The proper design of the tie-down is dependent on the accurate prediction of the wave slamming loads the cargo will experience during the voyage. This is a difficult task and model testing is a widely accepted and adopted method to obtain reliable sea-fastening loads and extreme accelerations. However, it is crucial to realize the difference in the inherent stiffness of the instrument that is used to measure the tri-axial sea fastening loads and the prototype design of the tie-downs. It is practically not possible to scale the tri-axial load measuring instrument stiffness to reflect the real tie-down stiffness during tests. A correlation method is required to systematically and consistently account for the stiffness differences and correct the measured results. Direct application of the measured load tends to be conservative and lead to over-design that can reflect on the overall cost and schedule of the project. The objective here is to employ the established correlation method to provide proper high-frequency responses to topsides and hull design teams. In addition, guidance for optimizing tie-down design to avoid damage to the installed equipment, facilities and structural members can be provided.

• Proceedings of the KSRS Conference
• /
• 2004.10a
• /
• pp.192-195
• /
• 2004

Products of gridded surface wind and windstress vectors over the world ocean have been constructed by satellite scatterometer data with highly temporal and spatial resolutions. Even if the ADEOS-II/SeaWinds has supplied surface wind data only for short duration in Apr. to Oct. 2003 to us, it permits us to construct a product with higher resolution together with the Qscat/SeaWinds. In addition to our basic product with its resolution of $1^{\circ}\times1^{\circ}$ in space and daily in time, we try to construct products with $1/2^{\circ}\times1/2^{\circ}$ and semi- and quarter-daily resolution. These products are validated by inter-comparison with in-situ data (TAO and NDBC buoys), and also compared with numerical weather prediction(NWP) ones (NCEP reanalysis). Result reveals that our product has higher reliability in the study area than the NCEP's. For the open ocean regions in the middle and high latitudes where there are no in-situ data, we find that there are clear differences between them. Especially in the southern westerly region of 400-600S, the' wind-stress magnitudes by the NCEP are significantly larger than the others, suggesting that they are overestimated. We also calculate wind-stress curl field that is an important factor for ocean dynamics and focus its spatial character in the northwestern Pacific around Japan. Positive curl areas are found to cover from southwest to northeast in our focus region and almost correspond to the Kuroshio path. It is suggested that the vorticity field in the lower atmosphere is related to the upper oceanic one, and thus an aspect of air-sea interaction process.

• The Korean Journal of Applied Statistics
• /
• v.31 no.5
• /
• pp.611-620
• /
• 2018

Limitations on human and material resources make it is difficult to conduct Ammunition Stockpile Reliability Program (ASRP) tasks for the entire ammunition. Stockpile ammunition life prediction studies can contribute to efficient ASRP tasks. This study assess the shelf-life of ammunition, using survival analysis based on ASRP results for 60mm and 81mm mortar ammunition from 2003 to 2016. Traditional assessments often use solely storage duration as the only main independent variable; however, this assessment used other factors such as ammunition magazine shape and weather factors with the stockpile shelf-life as independent variables to conduct a Cox's proportional hazard model analysis. This was then followed by an assessment of ammunition magazine type, maximum temperature and rainfall factors influence on the shelf-life of 60mm and 81mm mortar ammunition. As a result, the type of ammunition magazine, maximum temperature and the rainfall influence the shelf-life of 60mm and 81mm mortar ammunition.

• The Journal of Information Systems
• /
• v.29 no.3
• /
• pp.35-52
• /
• 2020

Purpose Local governments in each region actively hold local festivals for the purpose of promoting the region and revitalizing the local economy. Existing studies related to local festivals have been actively conducted in tourism and related academic fields. Empirical studies to understand the effects of latent variables on local festivals and studies to analyze the regional economic impacts of festivals occupy a large proportion. Despite of practical need, since few researches have been conducted to predict the number of visitors, one of the criteria for evaluating the performance of local festivals, this study developed a model for predicting the number of visitors through various observed variables using a machine learning algorithm and derived its implications. Design/methodology/approach For a total of 593 festivals held in 2018, 6 variables related to the region considering population size, administrative division, and accessibility, and 15 variables related to the festival such as the degree of publicity and word of mouth, invitation singer, weather and budget were set for the training data in machine learning algorithm. Since the number of visitors is a continuous numerical data, random forest, Adaboost, and linear regression that can perform regression analysis among the machine learning algorithms were used. Findings This study confirmed that a prediction of the number of visitors to local festivals is possible using a machine learning algorithm, and the possibility of using machine learning in research in the tourism and related academic fields, including the study of local festivals, was captured. From a practical point of view, the model developed in this study is used to predict the number of visitors to the festival to be held in the future, so that the festival can be evaluated in advance and the demand for related facilities, etc. can be utilized. In addition, the RReliefF rank result can be used. Considering this, it will be possible to improve the existing local festivals or refer to the planning of a new festival.

• Journal of the Korean Geographical Society
• /
• v.45 no.3
• /
• pp.319-341
• /
• 2010

The purposes of this study are to classify heavy snowfall types in the Republic of Korea based on fresh snowfall data and atmospheric circulation data during the last 36(1973/74-2008/09) snow seasons and to identify typical surface synoptic climate patterns that characterize each heavy snowfall type. Four synoptic climate categories and seventeen regional heavy snowfall types are classified based on sea level pressure/surface wind vector patterns in East Asia and frequent spatial clustering patterns of heavy snowfall in the Republic of Korea, respectively. Composite analyses of multiple surface synoptic weather charts demonstrate that the locations and intensity of pressure/wind vector mean and anomaly cores in East Asia differentiate each regional heavy snowfall type in Korea. These differences in synoptic climatic fields are primarily associated with the surge of the Siberian high pressure system and the appearance of low pressure systems over the Korean Peninsula. In terms of hemispheric atmospheric circulation, synoptic climatic patterns in the negative mode of winter Arctic Oscillation (AO) are also associated with frequent heavy snowfall in the Republic of Korea at seasonal scales. These results from long-term synoptic climatic data could contribute to improvement of short-range or seasonal prediction of regional heavy snowfall.

• Proceedings of the Korean Institute Of Construction Engineering and Management
• /
• 2004.11a
• /
• pp.472-475
• /
• 2004

The objective of this study is to develope reasonably accurate prediction models to assess hoisting times of tower cranes in the high-rise building construction. The efficient use of the tower crane is critical to achieving the Planned floor cycle time. This research describes the derivation of mathematical models to predict the hoisting times in using a tower crane. 28 factors such as nature of load, characteristics of tower cranes, hoisting movements, operation of cranes, weather conditions and so on is considered to influence hoisting times. In order to develop the predicting hoisting times Correctly, it is divided hoisting upward and downward. Then multiple regression models for predicting supply and return hoisting times have been built up separately.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.64 no.1
• /
• pp.128-135
• /
• 2015

In this study, we develop the very short-term precipitation forecasting model as well as classifier based on polynomial radial basis function neural networks by using AWS(Automatic Weather Station) and KLAPS(Korea Local Analysis and Prediction System) meteorological data. The polynomial-based radial basis function neural networks is designed to realize precipitation forecasting model as well as classifier. The structure of the proposed RBFNNs consists of three modules such as condition, conclusion, and inference phase. The input space of the condition phase is divided by using Fuzzy C-means(FCM) and the local area of the conclusion phase is represented as four types of polynomial functions. The coefficients of connection weights are estimated by weighted least square estimation(WLSE) for modeling as well as least square estimation(LSE) method for classifier. The final output of the inference phase is obtained through fuzzy inference method. The essential parameters of the proposed model and classifier such ad input variable, polynomial order type, the number of rules, and fuzzification coefficient are optimized by means of Particle Swarm Optimization(PSO) and Differential Evolution(DE). The performance of the proposed precipitation forecasting system is evaluated by using KLAPS meteorological data.

• Journal of Environmental Science International
• /
• v.21 no.4
• /
• pp.517-533
• /
• 2012

This study calculated wind speed at the height of 10 m using a disaster prediction model(Florida Public Hurricane Loss Model, FPHLM) that was developed and used in the United States. Using its distributions, a usable information of surface wind was produced for the purpose of disaster prevention when the typhoon attack. The advanced research version of the WRF (Weather Research and Forecasting) was used in this study, and two domains focusing on South Korea were determined through two-way nesting. A horizontal time series and vertical profile analysis were carried out to examine whether the model provided a resonable simulation, and the meteorological factors, including potential temperature, generally showed the similar distribution with observational data. We determined through comparison of observations that data taken at 700 hPa and used as input data to calculate wind speed at the height of 10 m for the actual terrain was suitable for the simulation. Using these results, the wind speed at the height of 10 m for the actual terrain was calculated and its distributions were shown. Thus, a stronger wind occurred in coastal areas compared to inland areas showing that coastal areas are more vulnerable to strong winds.