• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.17 no.2
• /
• pp.87-95
• /
• 2016

This study examined the characteristics of the hourly demand of city gas in Korea and proposed multiple regression models to obtain precise estimates of the hourly demand of city gas. Forecasting the hourly demand of city gas with accuracy is essential in terms of safety and cost. If underestimated, the pipeline pressure needs to be increased sharply to meet the demand, when safety matters. In the opposite case, unnecessary inventory and operation costs are incurred. Data analysis showed that the hourly demand of city gas has a very high autocorrelation and that the 24-hour demand pattern of a day follows the previous 24-hour demand pattern of the same day. That is, there is a weekly cycle pattern. In addition, some conditions that temperature affects the hourly demand level were found. That is, the absolute value of the correlation coefficient between the hourly demand and temperature is about 0.853 on average, while the absolute value of the correlation coefficient on a specific day improves to 0.861 at worst and 0.965 at best. Based on this analysis, this paper proposes a multiple regression model incorporating the hourly demand ahead of 24 hours and the hourly demand ahead of 168 hours, and another multiple regression model with temperature as an additional independent variable. To show the performance of the proposed models, computational experiments were carried out using real data of the domestic city gas demand from 2009 to 2013. The test results showed that the first regression model exhibits a forecasting accuracy of MAPE (Mean Absolute Percentage Error) around 4.5% over the past five years from 2009 to 2013, while the second regression model exhibits 5.13% of MAPE for the same period.

• Journal of the Korean Society of Marine Environment & Safety
• /
• v.28 no.5
• /
• pp.780-790
• /
• 2022

Quantitative risk levels must be presented by analyzing the causes and consequences of accidents and predicting the occurrence patterns of the accidents. For the analysis of marine accidents related to vessel traffic, research on the traffic such as collision risk analysis and navigational path finding has been mainly conducted. The analysis of the occurrence pattern of marine accidents has been presented according to the traditional statistical analysis. This study intends to present a marine accident prediction model using the statistics on marine accidents related to vessel traffic. Statistical data from 1998 to 2021, which can be accumulated by month and hourly data among the Korean domestic marine accidents, were converted into structured time series data. The predictive model was built using a long short-term memory network, which is a representative artificial intelligence model. As a result of verifying the performance of the proposed model through the validation data, the RMSEs were noted to be 52.5471 and 126.5893 in the initial neural network model, and as a result of the updated model with observed datasets, the RMSEs were improved to 31.3680 and 36.3967, respectively. Based on the proposed model, the occurrence pattern of marine accidents could be predicted by learning the features of various marine accidents. In further research, a quantitative presentation of the risk of marine accidents and the development of region-based hazard maps are required.

• Proceedings of the Korean Information Science Society Conference
• /
• 1999.10c
• /
• pp.265-267
• /
• 1999

이동 통신시스템을 시뮬레이션하기 위해서는 이동 통신에서 발생되는 호의 패턴을 분석하는게 매우 중요하다. 본 논문에서는 도시지역에 설치되어 있는 기지국의 지역특성을 고려한 이동 통신 통화량을 분석하여, 제시한다. 본 논문에서는 도시를 상업, 주거, 준공업 그리고 녹지 지역으로 되어 있는 도시계획 용도지역과 이외에 특이한 호 발생 패턴이 예측되는 역과 터널 주변이라는 6개의 지역으로 구분하고, 여기에 설치되어 있는 기지국으로부터 실제 데이터를 수집하였다. 이 자료를 이용하여 기지국이 설치되어 있는 지역에 따라 이동 통신 기지국의 시간대별 통화량 분포를 분석하였으며, 하루 중 통화량이 가장 많은 최빈시간대와 통화량이 가장 적은 최번시간대를 구하였다. 또한, 구해진 각 종 결과를 시뮬레이션에 적용하기 위한 평균값 및 분포값을 제시하였다. 이 파라메터들은 이동통신 시스템의 성능 및 신뢰성을 측정하기 위한 매우 중요한 값들이다.

• Proceedings of the KIEE Conference
• /
• 2008.11b
• /
• pp.69-71
• /
• 2008

에너지 다소비산업구조로 되어 있는 국내 산업시설 및 건축물 분야에서의 초에너지절약형 시스템으로의 개선이 절실하다. 전력다소비건물을 중심으로 대형건물의 시간대별 전력사용량과 년간 전력사용량을 조사하였고, 연면적, 계약전력, 최대수요전력 등의 전력소비 특성을 조사 분석하였다. 조사된 자료의 전체 특징과 중심적인 경향을 알아 보기 위해서 평균값, 표준편차, 최대값, 최소값, 중앙값 등의 특징파라메터를 분석하였다. 이를 토대로 에너지 성능 중심의 전력원단위 기준(안) 및 연간 전기에너지 사용 총량을 분석하였고, 전기에너지 연간사용총량 산정에 필요한 자료를 데이터베이스화하였다.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
• /
• v.23 no.6
• /
• pp.392-399
• /
• 2011

Ground-coupled heat pump(GCHP) systems have been shown to be an environmentally-friendly, efficient alternative to traditional cooling and heating systems in both residential and commercial applications. Although some work related to performance evaluation of GCHP systems for commercial buildings has been done, relatively little has been reported on the residential applications. The aim of this study is to evaluate the cooling and heating performances of a vertical GCHP system applied to an artificial detached house($117\;m^2$) in Seoul. For this purpose, a typical design procedure was involved with a combination of design parameters such as building loads, heat pump capacity, borehole diameter, and ground thermal properties, etc. The cooling and heating performance simulation of the system was conducted with different prediction times of 8760 hours and 240 months. The performance characteristics including seasonal system COP, average annual power consumption, and temperature variations related to ground heat exchanger were calculated and compared.

• Proceedings of the Korean Information Science Society Conference
• /
• 1998.10a
• /
• pp.101-103
• /
• 1998

뉴스기사를 구성하는 NOD데이터는 VOD(Video on Demand) 데이터와는 달리 미디어의 종류 및 크기, 시간적인 접근 지역성, 사용자와 상호 작용성 등의 차이점을 가질 뿐만 아니라 새로운 뉴스기사가 수시로 생성되고 사용자가 인기도가 높은 기사와 최신의 뉴스기사에 더 많이 접근하는 특성을 가진다. 본 논문에서는 현재 서비스중인 전자신문의 로그파일을 분석하여 NOD 뉴스기사의 인기도가 Zipf분포와 다름을 보이고, 뉴스기사의 생명주기Lifr Cycle)에 따른 접근 확률분포 제시한다. NOD 데이터의 접근 편기성으로 인하여 데이터 캐싱을 통한 NOD 서버의 성능 향상을 기대할 수 있으나 뉴스기사의 생명주기가 짧고 접근시간대별로 사용자 접근형태가 변하는 등의 이유로 단순히 인기도만 고려한 캐싱은 빈번한 데이터 재배치 문제로 인해 높은 캐시 관리비용을 야기한다. 따라서 본 논문에서는 뉴스 기사의 접근 편기성에 나타나는 인기도(popularity)와 생명주기를 조합한 척도를 제안하고 이를 이용한 재배치를 제안한다.

• Journal of Satellite, Information and Communications
• /
• v.10 no.4
• /
• pp.77-82
• /
• 2015

This paper proposed an accident prediction model in order to prevent accidents in mountain areas using a big data analysis. Data of accidents in mountain areas are shown as graphs. We have analyzed cases: the number of accidents per year, day of week, time of day to find patterns of the negligent accident in mountain areas. The proposed prediction model consists of weighted variables of the accident in mountain through visualized big data analysis. The model of danger index performance is demonstrated by showing accident-prone areas with weighted variables.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
• /
• v.23 no.6
• /
• pp.85-88
• /
• 2009

This paper shows a reasonable power density, that was made by the systematic and statistical way considering actual conditions, such as investigated power consumption capacity for the year and peak power, contract power for the last 5 years of each customer for 23 general customers all data obtained by AMR. In this dissertation, it is necessary to analyze the key features from the investigated data. It made an analysis of the feature parameters, such as average, standard deviation, median, maximum, minimun and load factor.

• The KIPS Transactions:PartC
• /
• v.10C no.4
• /
• pp.471-478
• /
• 2003

Traditionally,, analysis, simulation and measurement have all been used to evaluate the performance of network protocols and functional entities that support mobile wireless service. Simulation methods are useful for testing the complex systems which have the very complicate interactions between components. To develop a mobile call simulator which is used to examine, validate, and predict the performance of mobile wireless call procedures must have the teletraffic model, which is to describe the mobile communication environments. Mobile teletraffic model is consists of 2 sub-models, traffic source and network traffic model. In this paper, we analyzed the network traffic data which are gathered from selected Base Stations (BSs) to define the mobile teletraffic model. We defined 4 types of cell location-Residential, Commercial, Industrial, and Afforest zone. We selected some Base Stations (BSs) which are represented cell location types in Seoul city, and gathered real data from them And then, we present the call rate per hour, cail distribution pattern per day, busy hours, loose hours, the maximum number of call, and the minimum number of calls based on defined cell location types. Those parameters are very important to test the mobile communication system´s performance and reliability and are very useful for defining the mobile network traffic model or for working the existed mobile simulation programs as input parameters.

• The Korean Journal of Applied Statistics
• /
• v.22 no.6
• /
• pp.1177-1190
• /
• 2009

The traffic operating speed is one of important information to measure a road capacity. When we supply the information of the road of high traffic by using navigation, offering the present traffic information and the forecasted future information are the outstanding functions to serve the more accurate expected times and intervals. In this study, we proposed the traffic speed forecasting model using the accumulated traffic speed data of the road and highway and forecasted the average speed for each the road and high interval and each time interval using Fourier transformation and time series regression model with trigonometrical function. We also propose the proper method of missing data imputation and treatment for the outliers to raise an accuracy of the traffic speed forecasting and the speed grouping method for which data have similar traffic speed pattern to increase an efficiency of analysis.