• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.12 no.6
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• pp.1-9
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• 2013

The studies on the shortest path algorithms based on Dijkstra algorithm has been done continuously to decrease the time for searching. $A^*$ algorithm is the most represented one. Although fast searching speed is the major point of $A^*$ algorithm, there are high rates of failing in search of the shortest path, because of complex and irregular networks. The failure of the search means that it either did not find the target node, or found the shortest path, witch is not true. This study proposed $A^*$ algorithm applying method that can reduce searching failure rates, preferentially organizing the relations between the starting node and the targeting node, and appling it in reverse according to the organized path. This proposed method may not build exactly the shortest path, but the entire failure in search of th path would not occur. Following the developed algorithm tested in a real complex networks, it revealed that this algorithm increases the amount of time than the usual $A^*$ algorithm, but the accuracy rates of the shortest paths built is very high.

• The Journal of the Acoustical Society of Korea
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• v.17 no.6
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• pp.37-42
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• 1998

본 논문에서는 SCHMM에 적용된 관찰 확률 최대화에 의한 화자 적응 알고리즘을 제안한다. 제안된 알고리즘은 SCHMM의 관찰 확률 밀도들이 새로운 화자의 음성 특징을 잘 표현하지 못하는 경우 인식 성능이 저하되는 것을 막기 위하여, 적응 데이터의 각 특징 벡터들이 최대의 관찰 확률을 가질 수 있도록 관찰 확률 밀도를 결정하는 평균 벡터 μ와 분산 행렬 Σ를 기울기 탐색(gradient search) 알고리즘에 의해 반복적으로 적응시켜 주는 방법이다. SCHMM의 상태 천이 확률 A와 혼합 밀도 계수 C는 관찰 확률 밀도 적응 과정 을 거친 후, 적응 데이터로부터 구한 확률과 기존 확률의 가중 평균을 취하는 과정을 반복 하여 적응시켜 주었다. 제안된 화자 적응 알고리즘을 사용하여 단독음 인식 실험을 수행한 결과, 화자 적응을 수행하지 않았을 때와 비교하여 화자 독립 시스템에서는 평균 9.8%, 남 성 화자 종속 시스템에서는 평균 46.0%, 여성 화자 종속 시스템에서는 평균 52.7%의 인식 률 향상을 보였다.

• Korean Journal of Cognitive Science
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• v.32 no.3
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• pp.117-139
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• 2021

The way of change detection in which presence of a different item is determined between memory and test arrays with a brief in-between time interval resembles how visual search is done considering that the different item is searched upon the onset of a test array being compared against the items in memory. According to the resemblance, the present study examined whether varying the probability of change occurrence in a visual short-term memory-based change detection task can influence the aspect of response-decision making (i.e., change prevalence effect). The simple-feature change detection task in the study consisted of a set of four colored boxes followed by another set of four colored boxes between which the participants determined presence or absence of a color change from one box to the other. The change prevalence was varied to 20, 50, or 80% in terms of change occurrences in total trials, and their change detection errors, detection sensitivity, and their subsequent RTs were analyzed. The analyses revealed that as the change prevalence increased, false alarms became more frequent while misses became less frequent, along with delayed correct-rejection responses. The observed change prevalence effect looks very similar to the target prevalence effect varying according to probability of target occurrence in visual search tasks, indicating that the background principles deriving these two effects may resemble each other.

• Journal of Digital Convergence
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• v.13 no.9
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• pp.201-208
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• 2015

With services such as SNS and facebook, Big Data popularize the use of small size such as micro blogs are increasing. However, the problem of accuracy and computational cost of the search result of big data of a small size is unresolved. In this paper, we propose a subnet selection techniques based probability to improve the browsing speed of the small size of the text information from big data environments, such as micro-blogs. The proposed method is to configure the subnets to give to the attribute information of the data increased the probability data search speed. In addition, the proposed method improves the accessibility of the data by processing a pair of the connection information between the probability of the data constituting the subnet to easily access the distributed data. Experimental results showed the proposed method is 6.8% higher detection rates than CELF algorithm, the average processing time was reduced by 8.2%.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.6
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• pp.711-718
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• 2019

BDD is a well-known alternative to the conventional Boolean logic method in fault tree analysis. As the size of fault tree increases, the calculation time and computer resources for BDD dramatically increase. A new failure path search and path restructure method is proposed for efficient calculation of CS and MCS from BDD. Failure path grouping and bottom-up path search is proved to be efficient in failure path search in BDD and path restructure is also proved to be used in order to reduce the number of CS comparisons for MCS extraction. With these newly proposed methods, the top event probability can be calculated using the probability by ASDMP(Approximate Sum of Disjoint MCS Products), which is shown to be equivalent to the result by the conventional MCUB(Minimal Cut Upper Bound) probability.

• The Journal of the Korea Contents Association
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• v.21 no.8
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• pp.10-19
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• 2021

In CCVN, the existing content search and delivery protocols based on single-hop or multi-hop cause low content search ratio and high network traffic overhead. This paper proposes a RSU-based protocol for efficient content search and delivery. In the proposed protocol, an RSU chooses the candidate provider vehicle that provides the cost-minimized content delivery to the content requester vehicle. Simulation results verify that the proposed protocol achieves better performances.

• Journal of the Korea Society for Simulation
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• v.23 no.1
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• pp.33-42
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• 2014

In this paper we analyzed the search patterns for the anti-submarine warfare (ASW) surface ships cooperating with ASW helicopters. For this purpose, we modeled evasive motion of a submarine with a probabilistic method. And maneuvers and search actions of ships and helicopters participating in the anti-submarine search mission are designed. And for each simulation scenario, the case where a ship and a helicopter searches a submarine independently according to its optimized search pattern is compared with the case where the search platforms participate in the ASW mission cooperatively. Based on the simulation results, we proposed the reconfigured search patterns that help cooperative ASW surface ships increase the total cumulative detection probability (CDP).

• Journal of KIISE:Software and Applications
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• v.31 no.2
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• pp.164-172
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• 2004

For a local search algorithm to find a bettor quality solution it is required to generate and evaluate a sufficiently large number of candidate solutions as neighbors at each iteration, demanding quite an amount of CPU time. This paper presents a method of selectively generating only good-looking candidate neighbors, so that the number of neighbors can be kept low to improve the efficiency of search. In our method, a newly generated candidate solution is probabilistically selected to become a neighbor based on the quality estimation determined heuristically by a very simple evaluation of the generated candidate. Experimental results on the problem of load balancing for production scheduling have shown that our candidate selection method outperforms other random or greedy selection methods in terms of solution quality given the same amount of CPU time.

• Journal of the Korea Institute of Military Science and Technology
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• v.2 no.1
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• pp.90-100
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• 1999

유전자 알고리즘은 전통적인 등반 알고리즘을 이용하여 구하기 어려웠던 최적화 문제를 해결하기 위한 강인한(Robust) 탐색 기법이다. 특히 목적함수가 (1)여러 개의 국부 최대치를 가지는 경우, (2)수학적으로 표현이 불가능하거나 어려운 경우, (3)목적함수에 교란 항(disturbance term)이 섞여 있을 경우도 우수한 탐색 능력을 갖는 것으로 알려져 있다. 본 논문에서는 유전자 알고리즘을 이용하여 나타나는 다양한 해집합을 형성하는 개체군을 군집성 분석(cluster analysis)을 이용하여 군집화하고, 각 군집에 부여된 군집 적합도에 따라서 최적해를 구함으로써 단순 유전자 알고리즘에 의한 최적화보다 훨씬 향상된 탐색 알고리즘을 제안하였다. 반응표면의 형태가 정형화한 테스트 함수의 형태로 나타난다고 가정한 경우에 대하여 몬테 칼로 시뮬레이션을 통하여 본 알고리즘을 적용하여 평가하고 분석하였다.

• Proceedings of the KIEE Conference
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• 1998.07c
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• pp.1200-1202
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• 1998

전력 사업자들은 일반 수용가에 대한 공급 신뢰도를 개선하기 위해서 배전 자동화 시스템을 도입, 실시간 고장구간 탐색 및 계통 재구성을 추진하고 있다. 그러나. 고장 감지기 자체의 오동작이나 통신상의 오류, 다중사고의 가능성 등 불확실성을 포함하고 있기 때문에 비상시 사고구간 추정에 많은 노력과 시간비용이 요구될 수 있다. 따라서. 본 연구에서는 확률론과 휴리스틱 탐색법을 이용하여 배전자동화 시스템에 수집된 정보가 불확실성을 포함하는 경우에도 신속하게 사고 예비 후보 지역을 제시함으로써 고장구간 추정시간을 최소화 할 수 있는 전문가 시스템이 개발된다.