• Journal of Computing Science and Engineering
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• v.1 no.2
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• pp.162-176
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• 2007

Machine Learning (ML) has become very popular within Data Mining (KDD) and Artificial Intelligence (AI) research and their applications. In the ML and KDD contexts, two main approaches can be used for inducing a Bayesian Network (BN) from data, namely, Conditional Independence (CI) and the Heuristic Search (HS). When a BN is induced for classification purposes (Bayesian Classifier - BC), it is possible to impose some specific constraints aiming at increasing the computational efficiency. In this paper a new CI based approach to induce BCs from data is proposed and two algorithms are presented. Such approach is based on the Markov Blanket concept in order to impose some constraints and optimize the traditional PC learning algorithm. Experiments performed with the ALARM, as well as other six UCI and three artificial domains revealed that the proposed approach tends to execute fewer comparison tests than the traditional PC. The experiments also show that the proposed algorithms produce competitive classification rates when compared with both, PC and Naive Bayes.

• Nuclear Engineering and Technology
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• v.34 no.1
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• pp.68-79
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• 2002

The approach for evaluating the critical heat flux (CHF) margin using the departure from nucleate boiling ratio (DNBR) concept has been widely applied to PWR core design, while DNBR in this approach does not indicate appropriately the CHF margin in terms of the attainable power margin-to-CHF against a reactor core condition. The CHF power margin must be calculated by increasing power until the minimum DNBR reaches a DNBR limit. The Critical Power Ratio (CPR), defined as the ratio of the predicted CHF power to the operating power, is considered more reasonable for indicating the CHF margin and can be calculated by a CPR orrelation based on the heat balance of a test bundle. This approach yields directly the CHF power margin, but the calculated CPR must be corrected to compensate for many local effects of the actual core, which are not considered in the CHF test and analysis. In this paper, correction of the calculated CPR is made so that it may become equal to the DNB overpower margin. Exemplary calculations showed that the correction tends to be increased as power distribution is more distorted, but are not unduly large.

• Journal of Korean Society of Transportation
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• v.23 no.3 s.81
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• pp.35-47
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• 2005

This paper is to review a literature concerning Bus Transit Route Network Design(BTRNDP), to describe a future study direction for a systematic application for the BTRNDP. Since a bus transit uses a fixed route, schedule, stop, therefore an approach methodology is different from that of auto network design problem. An approach methodology for BTRNDP is classified by 8 categories: manual & guideline, market analysis, system analytic model. heuristic model. hybrid model. experienced-based model. simulation-based model. mathematical optimization model. In most previous BTRNDP, objective function is to minimize user and operator costs, and constraints on the total operator cost, fleet size and service frequency are common to several previous approach. Transit trip assignment mostly use multi-path trip assignment. Since the search for optimal solution from a large search space of BTRNDP made up by all possible solutions, the mixed combinatorial problem are usually NP-hard. Therefore, previous researches for the BTRNDP use a sequential design process, which is composed of several design steps as follows: the generation of a candidate route set, the route analysis and evaluation process, the selection process of a optimal route set Future study will focus on a development of detailed OD trip table based on bus stop, systematic transit route network evaluation model. updated transit trip assignment technique and advanced solution search algorithm for BTRNDP.

• Journal of the Korean Operations Research and Management Science Society
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• v.13 no.2
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• pp.25-33
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• 1988

An efficient heuristic solution procedure is developed for the minimum location problems. The gradient direction method and modified gradient approach are developed due to the differentiability of the objective functions. Suboptimal step size is obtained analytically. A Modified Gradient Procedure (NGP) is presented and compared with the hyperboloid approximation procedure (HAP) which is one of the best known methods.

• Review of KIISC
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• v.28 no.2
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• pp.12-19
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• 2018

사이버 침해공격은 단순히 사이버 공간에만 피해를 주는 것이 아니라, IoT/CPS와 연결되면서 실생활에 큰 피해를 줄 수 있는 중요한 문제로 대두되었다. 이러한 사이버 침해공격의 대부분은 악성코드를 사용하고 있으며, 점차 지능화된 형태로 발전하고 있다. 이에 대응하고자 다양한 악성코드 분석기술이 출현해왔으며, 최근의 연구들은 대부분 머신러닝을 이용하여 기존에 진행했던 Pattern, Heuristic 기반의 한계들을 보완하려 노력하고 있다. 본 논문에서는 머신러닝을 이용한 악성코드 분석기술의 동향을 기술하였다. 특히, 머신러닝을 이용한 악성코드 분석 목적을 7개로 분류하였고, 악성코드 분석에 핵심이 되는 Key Feature들에 대해 소개하였다. 본 논문을 통해, 다양한 악성코드 분석 방법에 있어 새로운 Approach로 연결되는 계기가 되기를 기대한다.

• Journal of the Korean Operations Research and Management Science Society
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• v.19 no.2
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• pp.177-198
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• 1994

We consider an algorithm for the Crew Scheduling Problem (CSP) based on the Transportation Problem approach. The main flows of the algorithm are arranged in three steps. First we propose a heuristic algorithm of the greedy principle to obtain an initial feasible solution. Secondary we present a method of formulating CSP into a Modified Transportation Problem format. Lastly the procedures of network search to get the optimal solution are presented. This algorithm can be applied to the general GSP and also to most combinatorial problems like the Vehicle Routing Problems. The computational results show that the large size CSP's could be tackled.

• Journal of the Korean Statistical Society
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• v.23 no.1
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• pp.89-102
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• 1994

A new method for approximating the average run length (ARL) of cumulative sum (CUSUM) chart is proposed. This method uses the conditional expectation for the test statistic before the stopping time and its asymptotic conditional density function. The values obtained by this method are compared with some other methods in normal and exponential case.

• Proceedings of the Korea Multimedia Society Conference
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• 2001.11a
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• pp.890-895
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• 2001

In this paper, we address on the problem of automatic scheduling and motion generation of multiple mobile robots fur collecting material parts. We propose a model and so]union algorithm for the system. The formulated problem is divided into two kinds of problems; assignment problem and planning problem of robot motion. In this paper, several approaches to solution methods are presented and compared through computer simulation.

• Journal of the Korean Operations Research and Management Science Society
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• v.18 no.1
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• pp.97-117
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• 1993

This paper considers inspection station location problem for a flexible assembly line that consists of multiple stages. By considering the trade-off between locating an station at an "early" stage and at a "late" stage, we have developed some dominance relations on a graph. Based on the dominance relations, we then present an algorithm that finds an optimal inspection plan and a heuristic approach that finds a near-optimal inspection plan. The effectiveness of these two algorithms is demonstrated by two numerical examples. numerical examples.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.11a
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• pp.273-276
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• 2006

At an integrated steel mill, various raw material such as coal and iron ore are unloaded from a large ship. The unloaded raw material is then transported to storage yards through a complex belt conveyer network. We propose an optimization model for scheduling the unloading operations under the limitations of available berths, unloading equipments and transportation capacity of the belt conveyer network. We show that the problem is NP-Hard and propose a heuristic approach to the problem.