• 한국멀티미디어학회논문지
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• 제12권12호
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• pp.1819-1826
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• 2009

To enhance the automatic performance of existing predicting and planning algorithms that require a predefined probability of the states' transition, this paper proposes a multiple sequence generation system. When interacting with unknown environments, a virtual agent needs to decide which action or action order can result in a good state and determine the transition probability based on the current state and the action taken. We describe a sequential behavior generation method motivated from the change in the agent's state in order to help the virtual agent learn how to adapt to unknown environments. In a sequence learning process, the sensed states are grouped by a set of proposed motivation filters in order to reduce the learning computation of the large state space. In order to accomplish a goal with a high payoff, the learning agent makes a decision based on the observation of states' transitions. The proposed multiple sequence behaviors generation system increases the complexity and heightens the automatic planning of the virtual agent for interacting with the dynamic unknown environment. This model was tested in a virtual library to elucidate the process of the system.

• 한국연소학회:학술대회논문집
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• 한국연소학회 2007년도 제34회 KOSCO SYMPOSIUM 논문집
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• pp.47-53
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• 2007

The laminar combustion characteristics of interacting coal particles in a convective flow are numerically investigated at particle arrangement and size difference. The numerical simulations, which use the two-step global reaction model to account for the surrounding gas effect, show the detailed interaction among the inter-space particles, undergoing devolatilization and subsequent char burning. Several parametric studies, which include the effect of the gas temperature (1700 K), high pressure(10 atm) and variation in geometrical arrangement of the particle diameter on the volatile release rate and the char combustion rate, have been carried out. The comparison indicates that the shift to the multiple particle arrangement resulted in the substantial change of the combustion characteristics and that the volatile release rate of the interacting coal particles exhibits a strong dependency on the particle spacing and size difference.

• Nuclear Engineering and Technology
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• 제53권2호
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• pp.532-548
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• 2021

Nuclear power plants contain several monitoring systems that can identify the in-vessel phenomena of a severe accident (SA). Though a lot of analysis and research is carried out on SA, right from the development of the nuclear industry, not all the possible circumstances are taken into consideration. Therefore, to improve the efficacy of the safety of nuclear power plants, additional analytical studies are needed that can directly monitor severe accident phenomena. This paper presents an interacting multiple model (IMM) based fault detection and diagnosis (FDD) approach for the identification of in-vessel phenomena to provide the accident propagation information using reactor vessel (RV) out-wall temperature distribution during severe accidents in a nuclear power plant. The estimation of wall temperature is treated as a state estimation problem where the time-varying wall temperature is estimated using IMM employing three multiple models for temperature evolution. From the estimated RV out-wall temperature and rate of temperature, the in-vessel phenomena are identified such as core meltdown, corium relocation, reactor vessel damage, reflooding, etc. We tested the proposed method with five different types of SA scenarios and the results show that the proposed method has estimated the outer wall temperature with good accuracy.

• International Journal of Aeronautical and Space Sciences
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• 제13권3호
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• pp.377-385
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• 2012

The Automatic Dependent Surveillance Broadcast (ADS-B) system is a key component of CNS/ATM recommended by the International Civil Aviation Organization (ICAO) as the next generation air traffic control system. ADS-B broadcasts identification, positional data, and operation information of an aircraft to other aircraft, ground vehicles and ground stations in the nearby region. This paper explores the ADS-B based trajectory prediction and the conflict detection algorithm. The multiple-model based trajectory prediction algorithm leads accurate predicted conflict probability at a future forecast time. We propose an efficient and accurate algorithm to calculate conflict probability based on approximation of the conflict zone by a set of blocks. The performance of proposed algorithms is demonstrated by a numerical simulation of two aircraft encounter scenarios.

• Management Science and Financial Engineering
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• 제6권2호
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• pp.1-28
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• 2000

Supply chain management issues faced by a manufacturing company are considered in this paper. The supply chain consists of a manufacturing company and its suppliers. The manufacturer produces multiple products with inputs (e.g., raw materials) from the suppliers, but each product needs a different mix of these inputs. The market demand for the products is uncertain. We develop a mathematical model and algorithm, which can help the manufacturer to solve its procurement decision problem: how much of raw material to order from which supplier. The model incorporates such factors as market demand uncertainty, product's input requirement, supplier's as well as manufacturer's capacity, plus other costs comparable with those in a typical newsboy problem. Numerical examples are presented to see the interacting effects among critical parameters and variables.

• 전기전자학회논문지
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• 제6권1호
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• pp.102-110
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• 2002

측정잡음이 시간에 순차적으로 상관된 경우의 동적 시스템에서의 다중 고장들을 검출하고 진단하는 효과적인 방법을 제시하였다. 제안된 고장검출 및 진단기법은 수정된 상호간섭다중모델 추정 알고리즘을 기반으로 하며 이것은 유색잡음에 대해 자기회귀 모델을 사용하고 측정 차분법을 적용함으로써 일반 비상관 프로세스를 설계하여 상호간섭다중모델 추정 알고리즘에 적용한 것이다.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2000년도 제13회 신호처리 합동 학술대회 논문집
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• pp.967-970
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• 2000

본 논문에서는 기동하는 표적을 추적하기 위한 표적의 운동 모델링 방법에 대해서 다룬다. 실제 표적의 운동은 진행방향으로의 가속과 이와는 독립적인 방향 전환으로 이루어진다는 점에 착안하여 표적의 진행방향에 따라 동작 잡음의 분산 행렬이 변화하는 표적 중심 모델을 제안하고, 이를 IMMPDAF(Interacting Multiple Model Probabilistic Data Association Filter)에 적용하였다. 모의실험을 통해 기존의 모델을 사용한 IMMPDAF와 비교하였으며, 그 결과 기동 구간의 오차가 30% 정도 줄어들며 추적 실패율도 낮아짐을 볼 수 있었다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.148-148
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• 2000

In this paper the IMM(Interacting Multiple model) algorithm using the MGEKF(Modified Gain Extended Kalman Filter) which modes are variances of the process noises is proposed to enhance the performance of maneuvering target tracking with bearing and frequency measurements. The state are composed of relative position, relative velocity, relative acceleration and doppler frequency. The mode probability is calculated from the bearing and frequency measurements. The proposed algorithm is tested a series of computer simulation runs.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2004년도 춘계학술대회 논문요약집
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• pp.166-166
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• 2004

운전자 보조시스템에는 적응순항제어 (adaptive cruise control), 차선변경 (lane change), 충돌경고 (collision warning), 충돌회피 (collision avoidance), 및 자동주차 (automatic parking) 등이 있다. 이런 운전자 보조시스템은 어떤 목적을 가지고 있다. 운전자의 부담을 줄이고 안전을 위하여 차량의 주행방향에 있는 장애물이나 차량을 감지하여 차량간의 안전거리론 유지하고 자동차가 일정 속도를 유지하도록 한다. 운전자 보조시스템의 효율은 센서들로부터 얻어진 정보의 해석에 달려있다.(중략)

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2003년도 통신소사이어티 추계학술대회논문집
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• pp.251-254
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• 2003

In this paper, we develop an effective method for estimating and predicting interference power strength using the IMM(Interacting Multiple Model) algorithm. Based on the proposed interference prediction algorithm, we adjust transmission power of mobile terminals to maintain a certain level of target signal - to - interference- plus -noise- ratio ( SINR ) at the base station. Results of numerical experiments are presented to show a performance profile of the proposed algorithm.