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Storm Sudden Commencements Without Interplanetary Shocks
Wooyeon Park,이정우,이유,Nicholas Ssessanga,SU YEON OH 한국우주과학회 2015 Journal of Astronomy and Space Sciences Vol.32 No.3
Storm sudden commencements (SSCs) occur due to a rapid compression of the Earth's magnetic field. This is generally believed to be caused by interplanetary (IP) shocks, but with exceptions. In this paper we explore possible causes of SSCs other than IP shocks through a statistical study of geomagnetic storms using SYM-H data provided by the World Data Center for Geomagnetism – Kyoto and by applying a superposed epoch analysis to simultaneous solar wind parameters obtained with the Advanced Composition Explorer (ACE) satellite. We select a total of 274 geomagnetic storms with minimum SYM-H of less than –30nT during 1998-2008 and regard them as SSCs if SYM-H increases by more than 10 nT over 10 minutes. Under this criterion, we found 103 geomagnetic storms with both SSC and IP shocks and 28 storms with SSC not associated with IP shocks. Storms in the former group share the property that the strength of the interplanetary magnetic field (IMF), proton density and proton velocity increase together with SYM-H, implying the action of IP shocks. During the storms in the latter group, only the proton density rises with SYM-H. We find that the density increase is associated with either high speed streams (HSSs) or interplanetary coronal mass ejections (ICMEs), and suggest that HSSs and ICMEs may be alternative contributors to SSCs.
Storm Sudden Commencements Without Interplanetary Shocks
Wooyeon Park,Jeongwoo Lee,Yu Yi,Nicholas Ssessanga,Suyeon Oh 한국우주과학회 2015 Journal of Astronomy and Space Sciences Vol.32 No.3
Storm sudden commencements (SSCs) occur due to a rapid compression of the Earth's magnetic field. This is generally believed to be caused by interplanetary (IP) shocks, but with exceptions. In this paper we explore possible causes of SSCs other than IP shocks through a statistical study of geomagnetic storms using SYM-H data provided by the World Data Center for Geomagnetism – Kyoto and by applying a superposed epoch analysis to simultaneous solar wind parameters obtained with the Advanced Composition Explorer (ACE) satellite. We select a total of 274 geomagnetic storms with minimum SYM-H of less than –30nT during 1998-2008 and regard them as SSCs if SYM-H increases by more than 10 nT over 10 minutes. Under this criterion, we found 103 geomagnetic storms with both SSC and IP shocks and 28 storms with SSC not associated with IP shocks. Storms in the former group share the property that the strength of the interplanetary magnetic field (IMF), proton density and proton velocity increase together with SYM-H, implying the action of IP shocks. During the storms in the latter group, only the proton density rises with SYM-H. We find that the density increase is associated with either high speed streams (HSSs) or interplanetary coronal mass ejections (ICMEs), and suggest that HSSs and ICMEs may be alternative contributors to SSCs.
Storm Sudden Commencements Without Interplanetary Shocks
Park, Wooyeon,Lee, Jeongwoo,Yi, Yu,Ssessanga, Nicholas,Oh, Suyeon The Korean Space Science Society 2015 Journal of Astronomy and Space Sciences Vol.32 No.3
Storm sudden commencements (SSCs) occur due to a rapid compression of the Earth's magnetic field. This is generally believed to be caused by interplanetary (IP) shocks, but with exceptions. In this paper we explore possible causes of SSCs other than IP shocks through a statistical study of geomagnetic storms using SYM-H data provided by the World Data Center for Geomagnetism - Kyoto and by applying a superposed epoch analysis to simultaneous solar wind parameters obtained with the Advanced Composition Explorer (ACE) satellite. We select a total of 274 geomagnetic storms with minimum SYM-H of less than -30nT during 1998-2008 and regard them as SSCs if SYM-H increases by more than 10 nT over 10 minutes. Under this criterion, we found 103 geomagnetic storms with both SSC and IP shocks and 28 storms with SSC not associated with IP shocks. Storms in the former group share the property that the strength of the interplanetary magnetic field (IMF), proton density and proton velocity increase together with SYM-H, implying the action of IP shocks. During the storms in the latter group, only the proton density rises with SYM-H. We find that the density increase is associated with either high speed streams (HSSs) or interplanetary coronal mass ejections (ICMEs), and suggest that HSSs and ICMEs may be alternative contributors to SSCs.
Simulation of One-way Carsharing Systems : Operating Parameters and Relocation Policy Analysis
SeJoon Park,Wooyeon Yu,Yunsun Park 한국산업경영시스템학회 2019 한국산업경영시스템학회지 Vol.42 No.3
The concept of carsharing involves sharing a small number of reserved cars to be used individually by a larger number of people as required. This study examines the operating parameters of one-way carsharing systems in order to determine the appropriate operating conditions that minimizes the lost sales rate. Five operating parameters are tested in this study: the number of stations, the average number of vehicles per station, the rate of one-way trip, the average number of staffs per station, and the relocation policy. The performance of round-trip carsharing systems is also compared to that of one-way carsharing systems. A simulation model is developed and simulations are performed to determine the appropriate combination of operating parameter and levels. The simulation results show that the average number of vehicles per station is the most critical parameter. Other key findings obtained from this research are as follows. First, applying the appropriate relocation policy to one-way carsharing systems can allow more customers to rent vehicles than the traditional round-trip carsharing systems. Second, the appropriate relocation policy should be selected based on the average number of vehicles per station in order to minimize the lost sales rate. Third, the number of stations does not affect the lost sales rate. This study findings will provide tools to understand impact of the carsharing system parameters on the efficiency of the carsharing operations.
시뮬레이션을 활용한 편도 카쉐어링 시스템의 최적 운영 조건 및 차량 재배치 알고리즘에 대한 연구
박세준(SeJoon Park),유우연(Wooyeon Yu),박윤선(Yunsun Park) 한국산업경영시스템학회 2019 한국산업경영시스템학회지 Vol.42 No.3
The concept of carsharing involves sharing a small number of reserved cars to be used individually by a larger number of people as required. This study examines the operating parameters of one-way carsharing systems in order to determine the appropriate operating conditions that minimizes the lost sales rate. Five operating parameters are tested in this study: the number of stations, the average number of vehicles per station, the rate of one-way trip, the average number of staffs per station, and the relocation policy. The performance of round-trip carsharing systems is also compared to that of one-way carsharing systems. A simulation model is developed and simulations are performed to determine the appropriate combination of operating parameter and levels. The simulation results show that the average number of vehicles per station is the most critical parameter. Other key findings obtained from this research are as follows. First, applying the appropriate relocation policy to one-way carsharing systems can allow more customers to rent vehicles than the traditional round-trip carsharing systems. Second, the appropriate relocation policy should be selected based on the average number of vehicles per station in order to minimize the lost sales rate. Third, the number of stations does not affect the lost sales rate. This study findings will provide tools to understand impact of the carsharing system parameters on the efficiency of the carsharing operations.
PSR: PSO-Based Signomial Regression Model
SeJoon Park,NagYoon Song,Wooyeon Yu,Dohyun Kim 한국지능시스템학회 2019 INTERNATIONAL JOURNAL of FUZZY LOGIC and INTELLIGE Vol.19 No.4
Regression analysis can be used for predictive and descriptive purposes in a variety of business applications. However, the successive existing regression methods such as support vector regression (SVR) have the drawback that it is not easy to derive an explicit function description that expresses the nonlinear relationship between an output variable and input variables. To resolve this issue, developed in this article is a nonlinear regression algorithm using particle swarm optimization (PSO) which is PSR. The output variables of PSR allow to obtain the explicit function description of the output variable using input variables. Three PSRs are proposed based on infeasible-particle update rules. Their experimental results show that the proposed approach performs similarly to and slightly better than the existing methods regardless of the data sets, implying that it can be utilized as a useful alternative when obtaining the explicit function description of the output variable using input variables and interpreting which of the original input variables are more important than others in the obtained regression model.