• 한국경영과학회지
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• 제19권2호
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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.

• 정보과학회 논문지
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• 제44권6호
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• pp.587-594
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• 2017

최근, 동작 상상(Motor Imagery) Electroencephalogram(EEG)를 기반으로 한 Brain-Computer Interface(BCI) 시스템은 의학, 공학 등 다양한 분야에서 많은 관심을 받고 있다. Common Spatial Pattern(CSP) 알고리즘은 동작 상상 EEG의 특징을 추출하기 위한 가장 유용한 방법이다. 그러나 CSP 알고리즘은 공분산 행렬에 의존하기 때문에 Small-Sample Setting(SSS) 상황에서 성능에 한계가 있다. 또한 사용하는 주파수 대역에 따라 큰 성능 차이를 보인다. 이러한 문제를 동시에 해결하기 위해, 4-40Hz 대역 EEG 신호를 9개의 필터 뱅크를 이용하여 분할하고 각 밴드에 Regularized CSP(R-CSP)를 적용한다. 이후 Mutual Information-Based Individual Feature(MIBIF) 알고리즘은 R-CSP의 차별적인 특징을 선택하기 위해 사용된다. 본 연구에서는 대뇌 피질의 운동영역 부근 18개 채널을 사용하여 BCI CompetitionIII DatasetIVa의 피험자 다섯 명(aa, al, av, aw 및 ay)에 대해 각각 87.5%, 100%, 63.78%, 82.14% 및 86.11%의 정확도를 도출하였다. 제안된 방법은 CSP, R-CSP 및 FBCSP 방법보다 16.21%, 10.77% 및 3.32%의 평균 분류 정확도 향상이 있었다. 특히, 본 논문에서 제안한 방법은 SSS 상황에서 우수한 성능을 보였다.

• 제어로봇시스템학회논문지
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• 제19권11호
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• pp.1022-1028
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• 2013

It is well knowns that based on the CSP (Common Spatial Pattern) algorithm, the linear projection of an EEG (Electroencephalography) signal can be made to spaces that optimize the discriminant between two patterns. Sharing disadvantages from linear time invariant systems, CSP suffers from the non-stationary nature of EEGs causing the performance of the classification in a BCI (Brain-Computer Interface) system to drop significantly when comparing the training data and test data. The author has suggested a simple idea based on the parallel model of CSP filters to improve the performance of BCI systems. The model was tested with a simple CSP algorithm (without any elaborate regularizing methods) and a perceptron learning algorithm as a classifier to determine the improvement of the system. The simulation showed that the parallel model could improve classification performance by over 10% compared to conventional CSP methods.

• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2004년도 봄 학술발표논문집 Vol.31 No.1 (A)
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• pp.25-27
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• 2004

시스템이 대형화가 되어가고 네트워크 환경이 발전함에 따라 분산 환경이 점점 더 증대되어 가고 있다. 이러한 분산 환경에서 사용되는 리더 선출 알고리즘(Leader Election Algorithm)은 다양하게 제시되었고 본 논문에서는 Garcia-Molina가 제시한 Bully 알고리즘을 프로세스 알제브라 언어인 CSP로 명세하고 FDR 모델체킹 도구를 이용해 해당 요구사항을 만족하는지 검증하였다.

• 산업경영시스템학회지
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• 제23권61호
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• pp.105-114
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• 2000

Job Shop Problem which consists of the m different machines and n jobs is a NP-hard problem of the combinatorial optimization. Each job consists of a chain of operations, each of which needs to be processed during an uninterrupted time period of a given length on a given machine. Each machine can process at most one operation at a time. The purpose of this paper is to develop the heuristic method to solve large scale scheduling problem using Constraint Satisfaction Problem method and Simulated Annealing. The proposed heuristic method consists of the search algorithm and optimization algorithm. The search algorithm is to find the solution in the solution space using CSP concept such as backtracking and domain reduction. The optimization algorithm is to search the optimal solution using SA. This method is applied to MT06, MT10 and MT20 Job Shop Problem, and compared with other heuristic method.

• 대한인간공학회:학술대회논문집
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• 대한인간공학회 1994년도 춘계학술대회논문집
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• pp.75-84
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• 1994

A control panel layout method based on the constraint satisfaction problem(CSP) technique was developed to generate an ergonomically sound panel design. This control panel layout method attempts to incorporate a variety of relevant ergonomic principles and design constrains, and generate an optimal or, at least, a "satisfactory" solution through the efficient search algorithm. The problem of seeking an ergonomically sound panel design should be viewed as a multiple criteria problem, and most of the design objectives should be understood as constraints. Hence, a CSP technique was employed in this study for dealing with the multi-constraiants layout problem. The efficient search algorithm using "preprocess" and "look ahead" procedures was developed to handle the vast amount of computational effort. In order to apply the CSP technique to the panel layout procedure, the ergonomic principles such as spatial compatibility, frequency-of- use, importance, functional grouping, and sequence-of-use were formalized as CSP terms. The effectiveness of the developed panel layout method was evaluated by example problems, and the results clearly showed that the generated layouts took various ergonomic design principles into account.esign principles into account.

• 대한안전경영과학회:학술대회논문집
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• 대한안전경영과학회 2004년도 춘계학술대회
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• pp.49-49
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• 2004

• 대한산업공학회지
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• 제20권4호
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• pp.85-97
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• 1994

An interactive and iterative control panel layout method based on the constraint satisfaction problem (CSP) technique was developed to generate an ergonomically sound panel design. This control panel layout method attempts to incorporate a variety of relevant ergonomic principles and design constraints, and generate an optimal or, at least, a "satisfactory" solution through an efficient search algorithm. The problem of seeking an ergonomically sound panel design should be viewed as a multi-criteria design problem and most of the design objectives should be understood as constraints. Hence, a CSP technique was employed in this study for dealing with the multi-constraints layout problem. The efficient search algorithm using "preprocess" and "look_ahead" procedures was developed to handle vast amount of computation. In order to apply the CSP technique to the panel layout procedure, the ergonomic principles such as spatial compatibility, frequency-of-use, importance, functional grouping, and sequence-of-use were formalized as CSP terms. The effectiveness of the proposed panel layout method was evaluated by example problems and the results clearly showed that the generated layouts properly considered various ergonomic design principles.

• IEIE Transactions on Smart Processing and Computing
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• 제4권2호
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• pp.97-102
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• 2015

In this paper, an extension of the standard common spatial pattern (CSP) algorithm using the strong uncorrelated transform (SUT) is used in order to extract the features for an accurate classification of the left- and right-hand motor imagery tasks. The algorithm is designed to analyze the complex data, which can preserve the additional information of the relationship between the two electroencephalogram (EEG) data from distant channels. This is based on the fact that distant regions of the brain are spatially distributed spatially and related, as in a network. The real-world left- and right-hand motor imagery EEG data was acquired through the Physionet database and the support vector machine (SVM) was used as a classifier to test the proposed method. The results showed that extracting the features of the pair-wise channel data using the strong uncorrelated transform complex common spatial pattern (SUTCCSP) provides a higher classification rate compared to the standard CSP algorithm.

• 한국컴퓨터정보학회논문지
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• 제20권9호
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• pp.105-111
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• 2015

This paper suggests O(n) linear-time algorithm for car sequencing problem (CSP) that has been classified as NP-complete because of the polynomial-time algorithm to solve the solution has been unknown yet. This algorithm applies maximum options-equiped car type first production rule to decide the car sequencing of n meet the r:s constraint. This paper verifies thirteen experimental data with the six data are infeasible. For thirteen experimental data, the proposed algorithm can be get the solution for in all cases. And to conclude, This algorithm shows that the CSP is not NP-complete but the P-problem. Also, this algorithm proposes the solving method to the known infeasible cases. Therefore, the proposed algorithm will stand car industrial area in good stead when it comes to finding a car sequencing plan.