• The KIPS Transactions:PartB
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• v.11B no.2
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• pp.213-220
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• 2004

Evolutionary algorithms are well-suited for multi-objective optimization problems involving several. often conflicting objective. Pareto-based evolutionary algorithms, in particular, have shown better performance than other multi-objective evolutionary algorithms in comparison. Recently, pareto-based evolutionary algorithms uses a density information in fitness assignment scheme for generating uniform distributed global pareto optimal front. However, the usage of density information is not Important elements in a whole evolution path but plays an auxiliary role in order to make uniform distribution. In this paper, we propose an evolutionary algorithms for multi-objective optimization which assigns the fitness using pareto dominance rank and density weighting, and thus pareto dominance rank and density have similar influence on the whole evolution path. Furthermore, the experimental results, which applied our method to the six multi-objective optimization problems, show that the proposed algorithms show more promising results.

• Journal of Korean Society of Transportation
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• v.26 no.4
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• pp.229-239
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• 2008

Most algorithms for detecting incidents have been developed under the premise that congestion must happen whenever an incident occurs. For that reason, the performance of these algorithms could not be guaranteed in cases where congestion did not happen due to traffic operations with low flows despite the occurrence of an incident. The objective of this paper is to develop an automatic incident detection algorithm using a new diagram that can reliably detect the incident under various conditions of traffic operations including a low volume state. Compared with the McMaster Algorithm, the proposed algorithm in this paper was evaluated with three different cases in which the incidents occur in traffic operations with a low volume state, a relatively high volume state, and a recurrent congestion state. It is shown that the new algorithm has a capability to identify the flow characteristics of incidents for all the three cases and is much better than McMaster algorithm in terms of detection rate and false alarm rate.

• Journal of the Korea institute for structural maintenance and inspection
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• v.23 no.5
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• pp.13-22
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• 2019

In order to evaluate the earthquake damage level of small and medium - sized bridges without earthquake monitoring system, we proposed an algorithm for estimating the seismic force at the target bridge location using the ground acceleration data from the earthquake observatories near the structure. In general, response spectrum analysis, which is the most widely used dynamic analysis method to design and evaluate the structural system numerically is required a response spectrum to determine the dynamic loading. In this study, selection methods of the three closest observatories from the target structure and estimation method of ground response spectrum at arbitrary locations are developed. The proposed method can consider the distance and phase between the target bridge and the seismic station and from the relationship between the acceleration amplitudes and the location of the selected seismic station, the earthquake loading of the target bridge can be determined. The proposed algorithm is estimated to be more conservative than the response spectrum evaluated by actual earthquake data.

• Journal of the Korean Geosynthetics Society
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• v.23 no.1
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• pp.27-37
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• 2024

In this study, direct algorithm-based back analysis was utilized to perform back analysis on two actual earth retaining wall fields, which was then compared with genetic algorithm-based method to evaluate the suitability of the back analysis. Additionally, in order to propose effective utilization methods of the program, the measurement data, as the input for the back analysis, was varied for each excavation step, and the applicability of the back analysis results(displacement, axial force) was examined. The research findings indicate that both direct algorithm and genetic algorithm show high applicability; however, the optimization for this program is better predicted by the direct algorithm. Moreover, in order to effectively use the back analysis program employing the direct algorithm, it was evaluated that relatively accurate prediction of the earth retaining wall behavior could be achieved by inputting measurement data from the 7th excavation step for fields with final excavation steps ranging from 8 to 11.

• Journal of Broadcast Engineering
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• v.14 no.2
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• pp.197-209
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• 2009

Stereoscopic video delivers depth perception to users contrary to 2D video. Therefore, we need to develop a new video quality assessment model for stereoscopic video. In this paper, we propose a new method for objective assessment of stereoscopic video. The proposed method detects blocking artifacts and degradation in edge regions such as in conventional video quality assessment model. And it detects video quality difference between views using depth information for efficient quality prediction. We performed subjective assessment of stereoscopic video to check the performance of the proposed method, and we confirmed that the proposed algorithm is superior to the existing method in PSNR in respect to correlation with results of the subjective assessment.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.6
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• pp.1961-1968
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• 2010

The Face Stimulus Assessment is an efficient projective drawing test developed by Betts. This paper categorizes scales which Betts suggested into the following five groups: accuracy of painting, color fit, perception of shape, precision of drawing, and space usage. In this paper, a computer algorithm which objectively evaluates these five scales is suggested. The proposed algorithm defines the areas of the lip, eyes, hair, etc. which take on significant roles in the evaluation of the FSA and based on these factors, it calculates the grade of each scale through the main color and color ratio. The consistency of evaluations between the computer algorithm and the art therapist is measured by the Quadratic Weighted Kappa. By providing objectivity and consistency, the computer algorithm is expected to solve the problem of uncertainty found in art therapists' evaluations of projective drawing tests caused by their subjective judgment, experience, and intuition.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.15 no.1
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• pp.127-136
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• 2002

This papers presents a practical damage detection algorithm based on damage index method that accurately assesses both the location and severity of the localized detriment in a bridge structure using only limited mode shapes. In the algorithm, the ratio of the modal vector sensitivity of an undamaged structure to that of a damaged structure is used as an indicator of damage. However, a difficulty arises when the damaged element is located at a node of mode where the amplitude of medal vector is close to zero, leading the singularity of the ratio (i.e., division-by-zero). This singularity problem is overcome by introducing a parameter denoted a sensitivity filter, a function of mode shape of the structure, in modal vector sensitivity. Using this concept, an improvement can be considerably achieved in the estimation of both degree of severity and location of damage. To verify the proposed algorithm, its numerical implementations are conducted for a simply supported beam and a 2-span continuous beam.

• Korean Journal of Cognitive Science
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• v.10 no.4
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• pp.51-62
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• 1999

This paper proposes a fuzzy Petri net representation to represent the fuzzy production rules of a rule-based expert system. Based on the fuzzy Petri net representation. we present a fuzzy reasoning algorithms which consist of forward and b backward reasoning algorithm. The proposed algorithms. which use the proper belief evaluation functions according to fuzzy concepts in antecedent and consequent of a fuzzy production rule. are more closer to human intuition and reasoning than other methods. The forward reasoning algorithm can be represented by a reachability tree as a kind of finite directed tree. The backward reasoning algorithm generates the backward reasoning path from the goal to the initial nodes and then evaluates the belief value of the goal node using belief evaluation functions.

• Journal of Digital Contents Society
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• v.8 no.1
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• pp.9-15
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• 2007

Smoothing is a transmission plan where variable rate video data is converted to a constant bit rate stream. Among them are CBA, MCBA, MVBA, e-PCRTT and others. e-PCRTT algorithm, which was improved from PCRTT, restricts the number of rate changes with fixed-size run. This causes unnecessary rate changes when run size is small and buffer size is large. In this paper, to overcome a shortcoming of e-PCRTT algorithm, a smoothing algorithm is proposed, which is improved from e-PCRTT, where a transmission rate transmits more intervalsl as possible. Experiments demonstrated that the proposed algorithm outperformed e-PCRTT algorithm. In order to show the performance, various evaluation factors were used such as the number of transmission rate changes, peak rate, transmission rate variability and so on.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.606-609
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• 2015

본 연구에서는 support vector regression (SVR) 및 매개변수 최적화 알고리즘을 이용한 하천수위 예측모델을 구축하고 이를 실제 유역에 적용하여 모델 효율성을 평가하였다. 여기서, SVR은 하천수위를 예측하기 위한 예측모델로서 채택되었으며, 커널함수 (Kernel function)로서는 radial basis function (RBF)을 선택하였다. 최적화 알고리즘은 SVR의 최적 매개변수 (C?, cost parameter or regularization parameter; ${\gamma}$, RBF parameter; ${\epsilon}$, insensitive loss function parameter)를 탐색하기 위하여 적용되었다. 매개변수 최적화 알고리즘으로는 grid search (GS), genetic algorithm (GA), particle swarm optimization (PSO), artificial bee colony (ABC) 알고리즘을 채택하였으며, 비교분석을 통해 최적화 알고리즘의 적용성을 평가하였다. 또한 SVR과 최적화 알고리즘을 결합한 모델 (SVR-GS, SVR-GA, SVR-PSO, SVR-ABC)은 기존에 수자원 분야에서 널리 적용되어온 신경망(Artificial neural network, ANN) 및 뉴로퍼지 (Adaptive neuro-fuzzy inference system, ANFIS) 모델과 비교하였다. 그 결과, 모델 효율성 측면에서 SVR-GS, SVR-GA, SVR-PSO 및 SVR-ABC는 ANN보다 우수한 결과를 나타내었으며, ANFIS와는 비슷한 결과를 나타내었다. 또한 SVR-GA, SVR-PSO 및 SVR-ABC는 SVR-GS보다 상대적으로 우수한 결과를 나타내었으며, 모델 효율성 측면에서 SVR-PSO 및 SVR-ABC는 가장 우수한 모델 성능을 나타내었다. 따라서 본 연구에서 적용한 매개변수 최적화 알고리즘은 SVR의 매개변수를 최적화하는데 효과적임을 확인할 수 있었다. SVR과 최적화 알고리즘을 이용한 하천수위 예측모델은 기존의 ANN 및 ANFIS 모델과 더불어 하천수위 예측을 위한 효과적인 도구로 사용될 수 있을 것으로 판단된다.