• 대한전기학회:학술대회논문집
• /
• 대한전기학회 2007년도 제38회 하계학술대회
• /
• pp.477-478
• /
• 2007

This paper proposes a new concept of support vector machine (SVM) based voltage stability classifier using time-series phasor data. The classifier, based on a linear SVM, can provide very effective signals for identification of long-term voltage stability. In addition, the SVM output is applicable as an voltage stability indicator when an amount of corrective controls are performed just to make the system reach around at the maximum deliverable point.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제8권11호
• /
• pp.4016-4027
• /
• 2014

Understanding network latency is important for providing consistent and acceptable levels of services in network-based applications. However, due to the difficulty of estimating applications' network demands and the difficulty of network latency modeling the management of network resources has often been ignored. We expect that, since network latency repeats cycles of congested states, a systematic classification method for network status would be helpful to simplify issues in network resource managements. This paper presents a simple empirical method to classify network status with a real operational network. By observing oscillating behavior of end-to-end latency we determine networks' status in run time. Five typical network statuses are defined based on a long-term stability and a short-term burstiness. By investigating prediction accuracies of several simple numerical models we show the effectiveness of the network status classification. Experimental results show that around 80% reduction in prediction errors depending on network status.

• 디지털융복합연구
• /
• 제11권10호
• /
• pp.305-311
• /
• 2013

경제시장의 규모가 지속적으로 발전함에 따라 올바른 의사결정을 위하여 경제시장을 정확하게 예측하는 문제가 중요한 문제로 떠오르고 있다. 현대 경제시스템을 표현하는 다양한 경제지표 중 가장 큰 축인 주식지표의 올바른 이해와 분석 그리고 의사결정문제에 적용을 위하여 시계열자료의 모델에 적합한 은닉마아코프모델과 이를 토대로 시계열자료의 시간 및 계산비용의 절감을 위한 차원감소기법들을 모델의 추정과 예측 문제에 적용하였으며 그 유효성을 확인하였다. 실험 결과, 은닉마아코프모델과 차원감소기법을 적용한 모델 모두에서 장기예측보다는 단기의 예측에서 최적의 모델 추정과 유사패턴 예측률이 모두 실제의 자료와 매우 유사함을 확인할 수 있었다.

• Journal of Information Technology Applications and Management
• /
• 제21권3호
• /
• pp.1-17
• /
• 2014

In this study, various characteristics of R&D related economic variables were studied to analyze complexity of science and technology activities in Korea, as reliance of R&D activities of the private sector is growing by the day. In comparison to other countries, this means that it is likely to be fluctuated by economic conditions. This complexity characteristic signifies that the result of science and technology activities can be greatly different from the anticipated results - depending on the influences from economic conditions and the results of science and technology activities which may be unpredictable. After reviewing the results of 17 variables related to science and technology characteristics of complex systems intended for time-series data - in the total R&D expenditure, and private R&D expenditure, numbers of SCI papers, the existence of chaotic characteristics were. using Lyapunov Exponent, Hurst Exponent, BDS test. This result reveals science and technology activity of the three most important components in Korea which are; heavy dependence on initial condition, the long term memory of time series, and non-linear structure. As stable R&D investment and result are needed in order to maintain steady development of Korea economy, the R&D structure should be less influenced by business cycles and more effective technology development policy for improving human resource development must be set in motion. And to minimize the risk of new technology, the construction of sophisticated technology forecasting system should take into account, for development of R&D system.

• 한국물환경학회지
• /
• 제24권3호
• /
• pp.345-353
• /
• 2008

In order to design storage-based non-point source management facilities, the aspect of statistical features of the entire precipitation time series should be considered since non-point source pollutions are delivered by continuous rainfall runoffs. The 3-parameter mixed exponential probability density function instead of traditional single-parameter exponential probability density function is applied to represent the probabilistic features of long-term precipitation time series and model urban stormwater runoff. Finally, probability density functions of water quality control basin overflow are derived under two extreme intial conditions. The 31-year continuous precipitation time series recorded in Busan are analyzed to show that the 3-parameter mixed exponential probability density function gives better resolution.

• 한국정보처리학회:학술대회논문집
• /
• 한국정보처리학회 2018년도 추계학술발표대회
• /
• pp.362-364
• /
• 2018

Predicting network traffic volume has become a popular topic recently due to its support in many situations such as detecting abnormal network activities and provisioning network services. Especially, predicting the volume of the next upcoming traffic from the series of observed recent traffic volume is an interesting and challenging problem. In past, various techniques are researched by using time series forecasting methods such as moving averaging and exponential smoothing. In this paper, we propose a long short-term memory neural network (LSTM) based network traffic volume prediction method. The proposed method employs the changing rate of observed traffic volume, the corresponding time window index, and a seasonality factor indicating the changing trend as input features, and predicts the upcoming network traffic. The experiment results with real datasets proves that our proposed method works better than other time series forecasting methods in predicting upcoming network traffic.

• Journal of the Korean Association of Oral and Maxillofacial Surgeons
• /
• 제41권3호
• /
• pp.156-164
• /
• 2015

Bilateral sagittal split ramus osteotomy is considered a standard technique in mandibular orthognathic surgeries to reduce unexpected bilateral stress in the temporomandibular joints. Unilateral sagittal split ramus osteotomy (USSO) was recently introduced to correct facial asymmetry caused by asymmetric mandibular prognathism and has shown favorable outcomes. If unilateral surgery could guarantee long-term postoperative stability as well as favorable results, operation time and the incidence of postoperative complications could be reduced compared to those in bilateral surgery. This report highlights three consecutive cases with long-term follow-up in which USSO was used to correct asymmetric mandibular prognathism. Long-term postoperative changes in the condylar contour and ramus and condylar head length were analyzed using routine radiography and computed tomography. In addition, prior USSO studies were reviewed to outline clear criteria for applying this technique. In conclusion, patients showing functional-type asymmetry with predicted unilateral mandibular movement of less than 7 mm can be considered suitable candidates for USSO-based correction of asymmetric mandibular prognathism with or without maxillary arch surgeries.

• 한국진공학회:학술대회논문집
• /
• 한국진공학회 2014년도 제46회 동계 정기학술대회 초록집
• /
• pp.484.2-484.2
• /
• 2014

There are many efforts to improving the power conversion efficiencies (PCEs) of dye-sensitized solar cells (DSCs). Although DSCs have a low production cost, their low PCE and low thermal stability have limited commercial applications. This study describes the preparation of a novel multifunctional polymer gel electrolyte in which a cross-linking polymerization reaction is used to encapsulate $TiO_2$ nanoparticles toward improving the power conversion efficiency and long-term stability of a quasi-solid state DSC. A series of liquid junction dye-sensitized solar cells (DSCs) was fabricated based on polymer membrane encapsulated dye-sensitized $TiO_2$ nanoparticles, prepared using a surface-induced cross-linking polymerization reaction, to investigate the dependence of the solar cell performance on the encapsulating membrane layer thickness. The ion conductivity decreased as the membrane thickness increased; however, the long term-stability of the devices improved with increasing membrane thickness. Nanoparticles encapsulated in a thick membrane (ca. 37 nm), obtained using a 90 min polymerization time, exhibited excellent pore filling among $TiO_2$ particles. This nanoparticle layer was used to fabricate a thin-layered, quasi-solid state DSC. The thick membrane prevented short-circuit paths from forming between the counter and the $TiO_2$ electrode, thereby reducing the minimum necessary electrode separation distance. The quasi-solid state DSC yielded a high power conversion efficiency (7.6/8.1%) and excellent stability during heating at $65^{\circ}C$ over 30 days. These performance characteristics were superior to those obtained from a conventional DSC (7.5/3.5%) prepared using a $TiO_2$ active layer with the same thickness. The reduced electrode separation distance shortened the charge transport pathways, which compensated for the reduced ion conductivity in the polymer gel electrolyte. Excellent pore filling on the $TiO_2$ particles minimized the exposure of the dye to the liquid and reduced dye detachment.

• 대한원격탐사학회지
• /
• 제39권6_2호
• /
• pp.1577-1589
• /
• 2023

해양의 모니터링을 위해서는 변화를 예측하는 과정이 필요하다는 것은 널리 인정되고 있다. 이 연구에서는 Geostationary Ocean Color Imager (GOCI) 자료를 이용하여 해양의 변화를 지시할 수 있는 반사도의 시계열 예측을 수행하였다. 이를 위해 다중 규모 Convolutional Long-Short-Term-Memory (ConvLSTM) 모델을 제안하였으며, GOCI-I 자료를 이용하여 모델을 학습하였다. 취득 기간이 다른 GOCI-II 자료를 이용하여 모델의 성능을 검증하였으며, 기존의 ConvLSTM 모델과 성능을 비교하였다. 비교 결과, 제안한 모델은 시공간적 특성을 모두 고려하여 반사도의 변화 경향성을 파악하는데 있어 가장 우수한 결과를 보였다. 장기 예측 결과를 통해 모델이 학습한 반사도의 시간적 변화 경향을 확인하였으며, 이를 이용한 주기적 변화 탐지가 가능할 것으로 기대된다.

• 한국항만경제학회지
• /
• 제34권1호
• /
• pp.81-98
• /
• 2018

우리나라의 경제발전은 무역을 주축으로 하고 있어 항만을 통한 물류가 필수적이다. 항만의 운영과 개발을 위해 막대한 자본과 시간이 투자되고 있으며 항만은 국가 경제 전반에 영향을 미치고 있다. 따라서 사회 경제적 손실을 방지하기 위해선 적정수준의 개발계획이 중요하다. 항만시설 계획은 항만 물동량 예측을 기반으로 수립되므로, 정확한 물동량 예측이 선행되어야 한다. 더불어 항만에서는 품목별로 취급 방식이 다르므로 품목별 예측이 이루어져야 구체적인 시설계획이 가능하다. 따라서 컨테이너 화물이나 항만 전체 물동량에 대해 주로 예측했던 선행 연구들과는 달리 본 논문에서는 전체 물동량에서 큰 비중을 차지하고 있는 유류화물을 분석 대상으로 설정하였다. 단기, 중장기의 주기적 특성과 추세를 갖고 있는 유류화물 물동량을 효율적으로 예측하고자 새로운 예측모형인 TSMR을 개발하였다. TSMR모형의 검증을 위해 기존의 시계열 모형들과 비교분석을 진행하였으며 ARIMA모형의 경우 물동량 데이터가 안정화되지 않아 유효한 결과를 산출할 수 없었다. 윈터스 가법, 단순계절모형과 비교하였을 때 단기적인 예측에는 다소 취약하였으나, TSMR모형의 전반적인 적합도와 예측력은 우수한 것으로 나타났다. 또한 철강, 유연탄, 기계류의 물동량 분석결과 TSMR모형의 일반화 가능성도 충분한 것으로 나타났다.