• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.14 no.4
• /
• pp.111-121
• /
• 2004

With rapid growth of the Internet, network intrusions have greatly increased and damage of attacks has become more serious. Recently some kinds of Internet attacks cause significant damage to overall network performance. Current Intrusion Detection Systems are not capable of performing the real-time detection on the backbone network In this paper, we propose the broadband network intrusion detection system using the exponential smoothing method. We made an experiment with real backbone traffic data for 8 days. The results show that our proposed system detects big jumps of traffic volume well.

• Journal of the Korean Institute of Gas
• /
• v.18 no.1
• /
• pp.8-16
• /
• 2014

In this study, the number of gas accidents prediction model was suggested by analyzing the gas accidents occurred in Korea. In order to predict the number of gas accidents, simple moving average method (3, 4, 5 period), weighted average method and exponential smoothing method were applied. Study results of the sum of mean-square error acquired by the models of moving average method for 4 periods and weighted moving average method showed the highest value of 44.4 and 43 respectively. By developing the number of gas accidents prediction model, it could be actively utilized for gas accident prevention activities.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.22 no.2
• /
• pp.276-283
• /
• 2018

Climate changes consistently cause coastal accidents such as coastal flooding, so the studies on monitoring the marine environments are progressing to prevent and reduce the damage from coastal accidents. In this paper, we propose a new method to predict the sea level which can be applied to coastal monitoring systems to observe the variation of sea level and warn about the dangers. Existing sea level models are very complicated and need a lot of tidal data, so they are not proper for real-time prediction systems. On the other hand, the proposed algorithm is very simple but precise in short period such as one or two hours since we use the measured data from the sensor. The proposed method uses Kalman filter algorithm for harmonic analysis and double exponential smoothing for additional error correction. It is shown by experimental results that the proposed method is simple but predicts the sea level accurately.

• Journal of Korean Society of Transportation
• /
• v.27 no.2
• /
• pp.47-56
• /
• 2009

Effective detection and correction of outliers of raw traffic data collected from the field is of keen interest because reliable traffic information is highly dependent on the quality of raw data. Global positioning system (GPS) based traffic surveillance systems are capable of producing individual vehicle speeds that are invaluable for various traffic management and information strategies. This study proposed a locally weighted regression (LWR) based filtering method for individual vehicle speed data. An important feature of this study was to propose a technique to generate synthetic outliers for more systematic evaluation of the proposed method. It was identified by performance evaluations that the proposed LWR-based method outperformed an exponential smoothing. The proposed method is expected to be effectively utilized for filtering out raw individual vehicle speed data.

• Journal of Korea Spatial Information System Society
• /
• v.11 no.2
• /
• pp.177-181
• /
• 2009

Developing u-Public facilities for application u-City is to combine both the state-of-the art of the construction and ubiquitous computing and must be flexibly comprised of the facilities for the basic service of the building such as air conditioning, heating, lighting and electric equipments to materialize a new format of spatial planning and the public facilities inside or outside. Accordingly, in this paper we suggested the time pattern system for predicting the most basic power system loads for the basic service. To application the tim e pattern we applied SOM algorithm and k-means method and then clustered the data each weekday and each time respectively. The performance evaluation results of suggestion system showed that the forecasting system better the ARIMA model than the exponential smoothing method. It has been assumed that the plan for power supply depending on demand and system operation could be performed efficiently by means of using such power load forecasting.

• Journal of Navigation and Port Research
• /
• v.31 no.6
• /
• pp.455-462
• /
• 2007

This paper estimated the future traffic volume incoming and outgoing in Incheon port, and analyzed the value of information serviced by tidal current signal operation center in Incheon. The cargo traffic in 2020 will increase twice as much as in 2005 according to the national ports basis plan. The maritime traffic will increase greatly consequently. Also, MOMAF has operated tidal current signal operation center to prevent marine accidents caused by current influence on vessels navigating through Incheon. However the quantitative effect is not known because there is no analysis about its value. Therefore the value of information serviced by tidal current signal operation center in Incheon was calculated with contingent valuation method(CVM), and the information value was analyzed considering future traffic in this study. Thus, the annual information value was calculated at about $170{\sim}280$ million won, considered traffic volume using the information of tidal current directly in 2020 since 2006.

• The Journal of the Korea Contents Association
• /
• v.19 no.1
• /
• pp.132-140
• /
• 2019

Recently, many cities around the world introduced and operated shared bicycle system to reduce the traffic and air pollution. Seoul also provides shared bicycle service called as "Ddareungi" since 2015. As the use of shared bicycle increases, the demand for bicycle in each station is also increasing. In addition to the restriction on budget, however, there are managerial issues due to the different demands of each station. Currently, while bicycle rebalancing is used to resolve the huge imbalance of demands among many stations, forecasting uncertain demand at the future is more important problem in practice. In this paper, we develop forecasting model for demand for Seoul shared bicycle using statistical time series analysis and apply our model to the real data. In particular, we apply Holt-Winters method which was used to forecast electricity demand, and perform sensitivity analysis on the parameters that affect on real demand forecasting.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.22 no.2
• /
• pp.284-294
• /
• 2018

Statistical methods have been widely used to estimate the remaining battery runtime of mobile smart devices, such as smart phones, smart gears, tablets, and etc. However, existing work available in the literature only considers a particular statistical method. Thus, it is difficult to determine whether statistical methods are applicable to estimating thr remaining battery runtime of mobile devices or not. In this paper, we evaluated the performance of statistical methods applicable to estimating the remaining battery runtime of mobile smart devices. The statistical estimation methods evaluated in this paper are as follows: simple and moving average, linear regression, multivariate adaptive regression splines, auto regressive, polynomial curve fitting, and double and triple exponential smoothing methods. Research results presented in this paper give valuable data of insight to IT engineers who are willing to deploy statistical methods on estimating the remaining battery runtime of mobile smart devices.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.8 no.1
• /
• pp.37-44
• /
• 2009

Density is the most important congestion indicator among the three fundamental flow variables, flow, speed and density. Measuring density in the field has two different ways, direct and indirect. Taking photos with wide views is one of direct ways, which is not widely used because of its cost and lacking of proper positions. Another direct density measuring method using two spot detectors has been introduced with the concept of instantaneous density, average density and measurement interval. The relationship between accuracy and measurement interval has been investigated using the simulation data produced by Paramics API function. Finally, density measurement algorithm has been suggested including exponential smoothing for device development.

• Journal of Digital Contents Society
• /
• v.18 no.4
• /
• pp.747-751
• /
• 2017

The log has variable informations that are important and necessary to manage a network when accessed to network servers. These informations are used to reduce a cost and efficient manage a network through the meaningful prediction information extraction from the amount of user access. And, the network manager can instantly monitor the status of CPU, memory, disk usage ratio on network using the SNMP. In this paper, firstly, we have accumulated and analysed the 6 network logs and extracted the informations that used to predict the amount of user access. And then, we experimented the prediction simulation with the time series analysis such as moving average method and exponential smoothing. Secondly, we have simulated the usage ration of CPU, memory, and disk using Xian SNMP simulator and extracted the OID for the time series prediction of CPU, memory, and disk usage ration. And then, we presented the visual result of the variable experiments through the Excel and R programming language.