• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1997.10a
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• pp.97-101
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• 1997

In recent years, there have been a number of applications of fuzzy logic in fuzzy reasoning system. The main objective of these applications is to approximate a decision making using the fuzzy reasoning system. This paper designs a fuzzy reasoning model for the decision making of registration fee at a private school, implements it applying for linguistic variables and fuzzy rules, and evaluates the practical availability of the model. The system accepts fuzzy rules, the type of membership functions, the domain of fuzzy sets and hedge, and fuzzifies the linguistic variables to generates fuzzy sets. The fuzzy sets generated are combined to constructs a solution fuzzy set. Finally, the system defuzzifies the solution fuzzy set to calculate a scalar value which is used for decision making.

• Proceedings of the KIEE Conference
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• 2004.07d
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• pp.2528-2530
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• 2004

Neural network minimization problems are often conditioned and in this contribution way to handle this will be discussed. It is shown that a better conditioned minimization problem can be obtained if the problem is separated with respect to the linear parameters. This will increase the convergence speed of the minimization. One of the most powerful uses of neural networks is in function approximation(curve fitting)[1]. A main characteristic of this solution is that function (f) to be approximated is given not explicitly but implicitly through a set of input-output pairs, named as training set, that can be easily obtained from calibration data of the measurement system. In this context, the usage of Neural Network(NN) techniques for modeling the systems behavior can provide lower interpolation errors when compared with classical methods like polynomial interpolation. This paper solve of single-variable minimization using neural network.

• Journal of the Korean Operations Research and Management Science Society
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• v.27 no.4
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• pp.67-86
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• 2002

This paper considers subway crew scheduling problem. Crew scheduling is concerned with finding a minimum number of assignments of crews to a given timetable satisfying various restrictions. Traditionally, crew scheduling problem has been formulated as a set covering or set partitioning problem possessing exponentially many variables, but even the LP relaxation of the problem is hard to solve due to the exponential number of variables. In this paper. we propose two basic techniques that solve the subway crew scheduling problem in a reasonable time, though the optimality of the solution is not guaranteed. We develop an algorithm that solves the column-generation problem in polynomial time. In addition, the integrality of the solution is accomplished by variable-fixing technique. Computational result for a real instance is reported.

• International Journal of Precision Engineering and Manufacturing
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• v.7 no.4
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• pp.57-62
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• 2006

The quality of precision spindle units (S/Us) running on rolling bearings depends strongly on their structural parameters, such as the configuration and geometry of the S/U elements and bearing preloads. When S/Us are designed, their parameters should be optimized to improve the performance characteristics. However, it is practically impossible to state perfectly a general criterion function for S/U quality. Therefore, we propose to use a multicriteria optimization based on the parameter space investigation (PSI) method We demonstrate the efficiency of the proposed method using the optimization results of high-speed S/Us.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.28 no.7
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• pp.871-878
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• 2004

An accurate adaptive mesh refinement based on the CIP method is proposed and it is applied to solve the two dimensional advection equations. In this method, the level set function is employed to refine and merge the computation cells. To enhance the accuracy of the solution, the spatial discretization is made by the CIP method. The CIP method has many advantages such as the third order accuracy, less diffusivity, and shape conserving. The mathematical formulation and numerical results are also described. To verify the efficiency, accuracy, and capability of the proposed algorithim, two dimensional rotating slotted cylinder and idealized frontogenesis are numerically simulated by the present scheme. As results, it is confirmed that the present method gives an efficient, reasonable solution in the advection equation.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2005.11a
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• pp.869-874
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• 2005

This paper proposes the Pareto artificial life algorithm for a multi-objective function optimization problem. The artificial life algorithm for a single objective function optimization problem is improved through incorporating the new method to estimate the fitness value fur a solution and the Pareto list to memorize and to improve the Pareto optimal set. The proposed algorithm is applied to the optimum design of a Journal bearing which has two objective functions. The Pareto front and the optimal solution set for the application are reported to present the possible solutions to a decision maker or a designer.

• Journal of the Korea Society of Computer and Information
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• v.24 no.9
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• pp.9-20
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• 2019

In this paper, we study the university timetabling problem, which consists of two subproblems, the university course timetabling problem and the examination timetabling problem. Given a set of classrooms, students, teachers, and lectures, the problem is to assign a number of courses (and examinations) to suitable timeslots and classrooms while satisfying the given set of constraints. We discuss the modeling and solution approaches to construct course and examination timetables for one of the largest Korean university. By using binary integer programming formulations, we describe these two complex real-world problems. Then, we propose a solution method, called NOGOOD, to solve the examination timetabling model. The computation results show that NOGOOD finds the optimal examination schedule for the given instance. Although we consider a specific instance of the university timetabling problem, the methods we use can be applicable to modeling and solving other timetabling problems.

• Current Optics and Photonics
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• v.5 no.3
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• pp.329-335
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• 2021

The problem of polarized light scattering by a cylinder on or close to a planar substrate is analytically solved. The light is assumed to be normally incident to the axis of the cylinder. Transverse magnetic (TM) and transverse electric (TE) polarizations are treated separately. The solution for each polarization is composed of a coupled set of linear equations which couples the scattering characteristics of the cylinder and the planar substrate. The coupling comes from the scattering by the planar substrate and by the cylinder. The solution of the coupled set of equations obtained by iterative substitution consists of infinite series, where each term represents the contribution of single and multiple scatterings of all orders.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.53 no.11
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• pp.596-603
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• 2004

This paper proposes an expert system based on the pattern recognition method which can enhance the accuracy and effectiveness of real-time bus reconfiguration strategy for the transfer of faulted load when a main transformer fault occurs in the automated substation. The minimum distance classification method is adopted as the pattern recognition method of expert system. The training pattern set is designed MTr by MTr to minimize the searching time for target load pattern which is similar to the real-time load pattern. But the control pattern set, which is required to determine the corresponding bus reconfiguration strategy to these trained load pattern set is designed as one table by considering the efficiency of knowledge base design because its size is small. The training load pattern generator based on load level and the training load pattern generator based on load profile are designed, which are can reduce the size of each training pattern set from max L/sup (m+f)/ to the size of effective level. Here, L is the number of load level, m and f are the number of main transformers and the number of feeders. The one reduces the number of trained load pattern by setting the sawmiller patterns to a same pattern, the other reduces by considering only load pattern while the given period. And control pattern generator based on exhaustive search method with breadth-limit is designed, which generates the corresponding bus reconfiguration strategy to these trained load pattern set. The inference engine of the expert system and the substation database and knowledge base is implemented in MFC function of Visual C++ Finally, the performance and effectiveness of the proposed expert system is verified by comparing the best-first search solution and pattern recognition solution based on diversity event simulations for typical distribution substation.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.10
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• pp.486-492
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• 2019

The system-based approach is needed to select an optimal mix of weapon systems and ship platform among a variety of design alternatives with the uncertainties of the initial required operational capability. In the early-phase design, which included a feasibility study and concept design, it is possible to cause problems when a review of the operational concept, database development, and systematic design are not done, thereby producing uncertain and unstable requirements. To select the best solution without trial-and-error, the U.S. navy has applied the set-based method for the early-phase design of a new ship-to-shore connector. The ship synthesis model plays an important role in applying the set-based method, but only a few countries possess this model and have prohibited this model from being transferred to other countries. This paper suggests a set-based method using a genetic algorithm and decision-making theory through benchmarking existing ship data. The algorithm was verified using the DDG-51 class ship synthesis model to optimize the weapon system design, which has been released for research purposes.