• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권12호
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• pp.5826-5841
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• 2019

In our previous research, we proposed a tag emotion-based item recommendation scheme. The ternary associations among users, items, and tags are described as a three-order tensor in order to capture the emotions in tags. The candidates for recommendation are created based on the latent semantics derived by a high-order singular value decomposition technique (HOSVD). However, the tensor is very sparse because the number of tagged items is smaller than the amount of all items. The previous research do not consider the previous behaviors of users and items. To mitigate the problems, in this paper, the item-based collaborative filtering scheme is used to build an extended data. We also apply the probabilistic ranking algorithm considering the user and item profiles to improve the recommendation performance. The proposed method is evaluated based on Movielens dataset, and the results show that our approach improves the performance compared to other methods.

• 대한안전경영과학회지
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• 제11권1호
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• pp.205-211
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• 2009

In reality, distribution planning for a supply chain is established using a certain probabilistic distribution estimated by forecasting. However, in general, the demands used for an actual distribution planning are of deterministic value, a single value for each of periods. Because of this reason the final result of a planning has to be a single value for each period. Unfortunately, it is very difficult to estimate a single value due to the inherent uncertainty in the probabilistic distribution of customer demand. The issue addressed in this paper is the selection of single demand value among of the distributed demand estimations for a period to be used in the distribution planning. This paper proposes an efficient demand selection scheme for minimizing total inventory costs while satisfying target service level under the various experimental conditions.

• 한국통신학회논문지
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• 제39B권3호
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• pp.188-190
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• 2014

MANET(Mobile Ad-hoc Networks)에서 참여 노드 수가 증가할수록 경로탐색을 위해 브로드캐스팅되는 제어메시지가 폭발적으로 증가하게 되어 네트워크 성능을 감소시킨다. 본 논문에서는 이런 브로드캐스트 스톰 문제(broadcast storm problem)의 발생 확률을 낮춰 네트워크 성능을 높일 수 있는 노드 상태 제어 알고리즘을 제안한다.

• 한국태양에너지학회 논문집
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• 제39권4호
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• pp.79-91
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• 2019

The capacity credit (CC) is a key metric for mid- to long-term power system capacity planning. The purpose of this study is to estimate the CCs of domestic wind turbines. Based on hourly capacity factor (CF) data during the seven years from 2011 to 2017, the new so-called probabilistic CF scheme is introduced to effectively reflect the variability of CFs on CC estimation. The CCs are then estimated through the CF-based method and the ELCC (Effective Load Carrying Capability) method reflecting the probabilistic CF scheme, and the results are compared. The results show that the CC value 0.019 for domestic wind turbines proposed in the $8^{th}$ Basic Plan for Electricity Supply and Demand corresponds to the CC with a confidence level slightly lower than 95%.

• 한국항행학회논문지
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• 제16권3호
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• pp.471-479
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• 2012

셀룰러 펨토 시스템에서 펨토 기지국(f-BS: femto base station)은 좁은 영역에 중복 설치 및 과밀 설치될 수 있다. 이러한 불필요한 설치는 채널을 공유하는 인접 f-BS간 간섭문제를 야기하여서 시스템의 용량과 커버리지에 영향을 미칠 수 있다. 본 논문은 셀룰러 펨토 시스템에서 발생할 수 있는 이러한 성능하락 문제를 해결하기 위하여 강제 핸드오버를 이용한 부하분산과 확률적 자원 이용방법을 제시한다. 제안하는 기법은 중앙 컨트롤러의 조정이 아닌 이웃 f-BS간의 통신을 통한 분산적인 방법이며, f-BS가 주변 정보를 수집하여 스스로 과밀지역에 분포하였음을 인식하고 부하 및 자원 이용의 조절하는 방법을 포함한다. 평균 셀 수율, 사용자당 평균 수율을 바탕으로 제안하는 기법의 성능 향상을 모의실험을 통해 검증하였다.

• 융합보안논문지
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• 제10권3호
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• pp.29-41
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• 2010

전장 지역에서 각종 전술정보를 실시간으로 수집할 수 있는 센서기반의 감시체계인 감시정찰 센서네트워크는 Sensor-to-Shooter 개념의 네트워크 중심전 환경에서 핵심 역할을 수행한다. 그러나 네트워크를 구성하는 센서노드들의 자원제약적 특성과 무선통신 사용 등 센서네트워크 자체의 특성으로 인해 감시정찰 센서네트워크는 일반 네트워크에 비해 보안이 취약해 질 수 있다. 이에 본 논문에서는 감시정찰 센서네트워크 운용 간 기밀성, 무결성, 가용성 및 인증 등을 보장하기 위한 기반이 되는 그룹 키 관리 기법을 제안한다. 제안된 키 관리 기법은 감시정찰 센서네트워크의 토폴로지 특성과 확률론적 키 공유를 기반으로 그룹 키를 생성하고 분배하며, 그룹 키분배에 소요되는 통신 비용은 O(logn)이다.

• 전기학회논문지
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• 제63권1호
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• pp.18-26
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• 2014

A microgrid can play a significant role for enlargement of renewable energy sources and emission reduction because it is a network of small, distributed electrical power generators operated as a collective unit. In this paper, an application of optimization method to economical operation of a microgrid is studied. The microgrid to be studied here is composed of distributed generation system(DGS), battery systems and loads. The distributed generation systems include combined heat and power(CHP) and small generators such as diesel generators and the renewable energy generators such as photovoltaic(PV) systems, wind power systems. Both of thermal loads and electrical loads are included here as loads. Also the emissions trading scheme to be applied in near future, the cost of unit start-up and the operational characteristics of battery systems are considered as well as the probabilistic characteristics of the renewable energy generation and load. A mathematical equation for optimal operation of this system is modeled based on the mixed integer programming. It is shown that this optimization methodology can be effectively used for economical operation of a microgrid by the case studies.

• 전기학회논문지
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• 제67권4호
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• pp.505-511
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• 2018

Long term capacity expansion planning has to be carried out to satisfy pre-defined system reliability criterion. For purpose of assessing system reliability, probabilistic simulation technique has been widely adopted. However, the way how to approximate generator outage, especially maintenance outage, in probabilistic simulation scheme can significantly influence on reliability assessment. Therefore, in this paper, 3 different maintenance approximation methods are applied to investigate the quantitative impact of maintenance approximation method on long term capacity expansion planning.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1998년도 The Third Asian Fuzzy Systems Symposium
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• pp.731-739
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• 1998

The probabilistic relaxation(PR) scheme based on the conditional probability and probability space partition has the important property that when its compatibility coefficient matrix (CCM) has uniform components it can classify m-dimensional probabilistic distribution vectors into different classes. When consistency or inconsistency measures have been defined, the properties of PRs are completely determined by the compatibility coefficients among labels of labeled objects and influence weight among labeled objects. In this paper we study the properties of PR in which both compatibility coefficients and influence weights are uniform, and then a learning rule for such PR system is derived. Experiments have been performed to verify the effectiveness of the learning rule.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2007년도 춘계학술대회논문집
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• pp.978-982
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• 2007

A new neuro-control scheme for active control of structures is proposed. It utilizes lattice pattern of state vector as training data of probabilistic neural network (PNN). Therefore, it is the so-called lattice probabilistic neural network (LPNN). PNN makes control forces by using all the training patterns. Therefore, it takes much time to obtain a control force in application. This inevitably may delay the control action. However, control force of LPNN is calculated by using only the adjacent information of LPNN input. So, the response of LPNN is greatly faster than PNN. The proposed control algorithm is applied for one story building under California and El Centro earthquakes. Also, control results of the LPNN are compared with those of the conventional PNN. The structural responses have been suppressed effectively by the proposed algorithm.