• 한국정보과학회논문지:시스템및이론
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• 제31권1_2호
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• pp.102-111
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• 2004

단순 다각형 P의 가시성 다각형을 점이나 에지와 같은 P에서의 가시원으로부터 가시적인 점들의 집합을 말한다. 가시성 다각형은 점들의 ,집합이므로 가시성 다각형들에 대해 교집합, 합집합, 차집합 등과 같은 집합 연산을 수행할 수 있다. 두 가시성 다각형의 교집합은 해당되는 두 가시원으로부터 동시에 보이는 점들의 집합이고, 합집합은 하나 이상의 가시원으로부터 보이는 점들의 집합이다. 두 가시성 다각형의 차집합은 하나의 가시원으로부터만 보이는 점들의 집합이다. 모두 n개의 정점을 가진 두 개의 일반적인 다각형에 대해 집합 연산을 수행하는 기존의 알고리즘으로 가장 효율적인 알고리즘은 O(nlogn + k) 시간이 소요된다, k는 집합 연산의 출력의 크기이다. 그러나 본 논문에서는 가시성 다각형의 특성을 이용하여 O(n) 시간에 교집합, 합집합, 차집합을 구하는 최적인 알고리즘을 제시한다.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1998년도 The Third Asian Fuzzy Systems Symposium
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• pp.288-295
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• 1998

This paper proposes a new data classification method based on the tolerant rough set that extends the existing equivalent rough set. Similarity measure between two data is described by a distance function of all constituent attributes and they are defined to be tolerant when their similarity measure exceeds a similarity threshold value. The determination of optimal similarity theshold value is very important for the accurate classification. So, we determine it optimally by using the genetic algorithm (GA), where the goal of evolution is to balance two requirements such that (1) some tolerant objects are required to be included in the same class as many as possible. After finding the optimal similarity threshold value, a tolerant set of each object is obtained and the data set is grounded into the lower and upper approximation set depending on the coincidence of their classes. We propose a two-stage classification method that all data are classified by using the lower approxi ation at the first stage and then the non-classified data at the first stage are classified again by using the rough membership functions obtained from the upper approximation set. We apply the proposed classification method to the handwritten numeral character classification. problem and compare its classification performance and learning time with those of the feed forward neural network's back propagation algorithm.

• 경영과학
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• 제23권1호
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• pp.75-85
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• 2006

The rectilinear Steiner tree problem (RSTP) is to find a minimum-length rectilinear interconnection of a set of terminals in the plane. It is well known that the solution to this problem will be the minimal spanning tree(MST) on some set Steiner points. The RSTP is known to be NP-complete. The RSTP has received a lot of attention in the literature and heuristic and optimal algorithms have been proposed. A key performance measure of the algorithm for the RSTP is the reduction rate that is achieved by the difference between the objective value of the RSTP and that of the MST without Steiner points. A hybrid evolutionary strategy on RSTP based upon nodes set is presented. The computational results show that the hybrid evolutionary strategy is better than the previously proposed other heuristic. The average reduction rate of solutions from the evolutionary strategy is about 11.14%, which is almost similar to that of optimal solutions.

• 한국멀티미디어학회논문지
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• 제22권2호
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• pp.203-209
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• 2019

The performance of an intelligent classifier for detecting malwares added to multimedia contents based on machine learning is highly dependent on the properties of feature set. Especially, in order to determine the malicious code in real time the size of feature set should be as short as possible without reducing the accuracy. In this paper, we introduce an optimal feature selection method to satisfy both high detection rate and the minimum length of feature set against the feature set provided by PEFeatureExtractor well known as a feature extraction tool. For the evaluation of the proposed method, we perform the experiments using Windows Portable Executables 32bits.

• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2004년도 가을 학술발표논문집 Vol.31 No.2 (2)
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• pp.703-705
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• 2004

Conventional support vector machines (SVMs) find optimal hyperplanes that have maximal margins by treating all data equivalently. In the real world, however, the data within a data set may differ in degree of uncertainty or importance due to noise, inaccuracies or missing values in the data. Hence, if all data are treated as equivalent, without considering such differences, the optimal hyperplanes identified are likely to be less optimal. In this paper, to more accurately identify the optimal hyperplane in a given uncertain data set, we propose a membership-induced distance from a hyperplane using membership values, and formulate three kinds of membership-induced SVMs.

• 한국시뮬레이션학회논문지
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• 제5권1호
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• pp.91-106
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• 1996

Control Variate (CV) is very useful technique for variance reduction in a wide class of queueing network simulations. However, the loss in variance reduction caused by the estimation of the optimum control coefficients is an increasing function of the number of control variables. Therefore, in some situations, it is required to select an optimal set of control variables to maximize the variance reduction . In this paper, we develop the Adaptive Control Variates (ACV) method which selects an optimal set of control variates during the simulation adatively. ACV is useful to maximize the simulation efficiency when we need iterated simulations to find an optimal solution. One such an example is the Simulated Annealing (SA) because, in SA algorithm, we have to repeat in calculating the objective function values at each temperature, The ACV can also be applied to the queueing network optimization problems to find an optimal input parameters (such as service rates) to maximize the throughput rate with a certain cost constraint.

• Structural Engineering and Mechanics
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• 제71권2호
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• pp.139-151
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• 2019

In a project schedule, it is possible to reduce the time required to complete a project by allocating extra resources for critical activities. However, accelerating a project causes additional expense. This issue is addressed by finding optimal set of time-cost alternatives and is known as the time-cost trade-off problem in the literature. The aim of this study is to identify the optimal set of time-cost alternatives using a multiobjective teaching-learning-based optimization (TLBO) algorithm integrated with the non-dominated sorting concept and is applied to successfully optimize the projects ranging from a small to medium large projects. Numerical simulations indicate that the utilized model searches and identifies optimal / near optimal trade-offs between project time and cost in construction engineering and management. Therefore, it is concluded that the developed TLBO-based multiobjective approach offers satisfactorily solutions for time-cost trade-off optimization problems.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1998년도 춘계학술대회 학술발표 논문집
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• pp.49-52
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• 1998

Neural Network has good performance in pattern classification, control and many other fields by learning ability. However, there is effective rule or systematic approach to determine optimal structure. In this paper, we propose a new method to find optimal structure of feed-forward multi-layer neural network as a kind of pruning method. That eliminating redundant elements of neural network. To find redundant elements we analysis error and weight changing with Rough Set Theory, in condition of executing back-propagation leaning algorithm.

• 대한조선학회논문집
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• 제45권2호
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• pp.221-228
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• 2008

This paper describes to determine optimum main particulars of warships which satisfy user's requirements in a concept design stage with minimum construction cost and maximum transportation efficiency. Present worth was used as an assessment criteria of the economical efficiency. And Pareto optimal set was used to have the optimum design.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1993년도 한국자동제어학술회의논문집(국제학술편); Seoul National University, Seoul; 20-22 Oct. 1993
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• pp.30-35
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• 1993

Simple recurrence relations for calculating completion times of various storage polices (unlimited, intermediate storages(FIS), finite intermediate storages(FIS), no intermediate storage(NIS), zero wait(ZW) for serial multi-product multi-unit processes are suggested. Not only processing times but also transfer times, set-up (clean-up) times of units and set-up times of storages are considered. Optimal scheduling strategies with zero transfer times and zero set-up times had been developed as a mixed integer linear programniing(MILP) formulation for several intermediate storage policies. In this paper those with non-zero transfer times, non-zero set-up times of units and set-up times of storages are newly proposed as a mixed integer nonlinear programming(MINLP) formulation for various storage polices (UIS, NIS, FIS, and ZW). Several examples are tested to evaluate the robustness of this strategy and reasonable computation times.