• 한국생산제조학회지
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• 제22권3호
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• pp.356-363
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• 2013

Mechanical molding press which is used for transformation process during semiconductor manufacturing process has structural deformations by pressure. If these deformations have over limit range, life of the press itself can be reduced and it will be exerted on a bad effect for quality of the semiconductor. In this research, the main plates and links of a press are analyzed in relation to the structural deformations caused by pressure excluding thermal deformations. After modifying the modeling, the analysis is performed again to determine optimal design of the press, and this design is introduced to ensure that most of the stresses on the main plates are within safe allowable limits. As a result, an optimal design method for the structure is investigated to produce the desired pressure even when the size of the main structure is minimized.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1991년도 하계학술대회 논문집
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• pp.333-336
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• 1991

In this paper, Hopfield & Tank model-like artificial neural network structure is proposed, which can be used for the optimal path planning problems such as the unit commitment problems or the maintenance scheduling problems which have been solved by the dynamic programming method or the branch and bound method. To construct the structure of the neural network, an energy function is defined, of which the global minimum means the optimal path of the problem. To avoid falling into one of the local minima during the optimization process, the simulated annealing method is applied via making the slope of the sigmoid transfer functions steeper gradually while the process progresses. As a result, computer(IBM 386-AT 34MHz) simulations can finish the optimal unit commitment problem with 10 power units and 24 hour periods (1 hour factor) in 5 minites. Furthermore, if the full parallel neural network hardware is contructed, the optimization time will be reduced remarkably.

• 한국정밀공학회지
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• 제17권2호
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• pp.176-184
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• 2000

Possible representation methods for the product structure have been compared and analyzed to determine optimal disassembly path of a product. Petri net is selected as the most optimal method to represent disassembly path of the product. In this method, a reachability tree for the product is generated and disassembly time for each path is calculated. A path with the smallest disassembly time is selected as the optimal path. A software far DPN(Disassembly Petri Net) has been developed and applied to search the optimal disassembly path for a ballpoint pen disassembly process as an example.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회 1996년도 추계학술대회발표논문집; 고려대학교, 서울; 26 Oct. 1996
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• pp.135-138
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• 1996

In solving the Travel Salesman Problem(TSP), we easily reach local optimal solutions with the existing methods such as TWO-OPT, THREE-OPT, and Lin-Kernighen. Tabu search, as a meta heuristic, is a good mechanism to get an optimal or a near optimal solution escaping from the local optimal. By utilizing AI concepts, tabu search continues to search for improved solutions. In this study, we focus on developing a new neighborhood structure that maintains the feasibility of the tours created by exchange operations in TSP. Intelligent methods are discussed, which keeps feasible tour routes even after exchanging several edges continuously. An extended tabu search model, performing cycle detection and diversification with memory structure, is applied to TSP. The model uses effectively the information gathered during the search process. Finally, the results of tabu search and simulated annealing are compared based on the TSP problems in the prior literatures.

• 유공압시스템학회논문집
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• 제7권3호
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• pp.20-27
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• 2010

A vehicle suspension system performs two functions, the ride quality and the stability, which conflict with each other. An active suspension system has an external energy source, from which energy is always supplied to the system for continuous control of vehicle motion. Therefore, an active suspension system can have even more improved performance. Some control laws have been proposed for active suspension system, but in this paper, an optimal variable structure control(VSC) is proposed. The VSC method is well suited for a class of nonlinear system and can address the robustness issues to constant modelling errors and disturbances. This paper develops an optimal VSC controller and compares its performance to those of a passive suspension system and an active suspension system with an optimal controller. The transient and frequency responses are analyzed respectively.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2001년도 춘계학술대회 논문집
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• pp.271-274
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• 2001

The present paper deals with the development of digital contouring controller for multiaxial servosystem. Instead of coordinating the commands to the individual feed drives and implementing closed position loop control for each axis, this work is achieved by the evaluation of a optimal cross-couple compensator aimed specifically at improving contouring accuracy in multi-axial feed drives. The optimal control formulation explicitly includes the contour error in the performance index to be minimized. The contouring control is simulated for straight line. The results show that the proposed controller reduces contouring errors considerably, as compared to the conventional uncoupled control for biaxial systems.

• Earthquakes and Structures
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• 제7권6호
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• pp.1025-1044
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• 2014

In this paper, a systematic technique is proposed for the optimal placement and design of nonlinear dampers for building structures. The concept of Output Frequency Response Function (OFRF) is applied to analytically represent the output frequency response of a building frame where nonlinear viscous dampers are fitted for suppression of vibration during earthquakes. An effective algorithm is derived using the analytical representation to optimally determine the locations and parameters of the nonlinear dampers. Various numerical examples are provided to verify the effectiveness of the optimal designs. A comparison of the vibration suppression performance with that of the frame structure under a random or uniform damping allocation is also made to demonstrate the advantages of the new designs over traditional solutions.

• 대한조선학회논문집
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• 제54권5호
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• pp.378-386
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• 2017

In this paper, a method is presented for the optimal design of submarine pressure hull structures by taking advantage of genetic algorithm techniques. The objective functions and design constraints in the process of structural optimization are based on the ultimate limit states of hull structures. One of the benefits associated with the utilization of genetic algorithm is that the optimization process can be completed within short generations of design variables for the pressure hull structure model. Applied examples confirm that the proposed method is useful for the optimal design of submarine pressure hull structures. Details of the design procedure with applied examples are documented. The conclusions and insights obtained from the study are summarized.

• Earthquakes and Structures
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• 제9권5호
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• pp.1115-1132
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• 2015

The study considers earthquake shake table testing of bending-torsion coupled structures under multi-component stationary random earthquake excitations. An experimental procedure to arrive at the optimal excitation cross-power spectral density (psd) functions which maximize/minimize the steady state variance of a chosen response variable is proposed. These optimal functions are shown to be derivable in terms of a set of system frequency response functions which could be measured experimentally without necessitating an idealized mathematical model to be postulated for the structure under study. The relationship between these optimized cross-psd functions to the most favourable/least favourable angle of incidence of seismic waves on the structure is noted. The optimal functions are also shown to be system dependent, mathematically the sharpest, and correspond to neither fully correlated motions nor independent motions. The proposed experimental procedure is demonstrated through shake table studies on two laboratory scale building frame models.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1999년도 하계학술대회 논문집 G
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• pp.2911-2913
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• 1999

This paper suggest an optimal identification method to complex and nonlinear system modeling that is based on Fuzzy-Neural Network(FNN). The FNN modeling implements parameter identification using HCM algorithm and optimal identification algorithm structure combined with two types of optimization theories for nonlinear systems, we use a HCM Clustering Algorithm to find initial parameters of membership function. The parameters such as parameters of membership functions, learning rates and momentum coefficients are adjusted using optimal identification algorithm. The proposed optimal identification algorithm is carried out using both a genetic algorithm and the improved complex method. Also, an aggregate objective function(performance index) with weighted value is proposed to achieve a sound balance between approximation and generalization abilities of the model. To evaluate the performance of the proposed model, we use the time series data for gas furnace, the data of sewage treatment process and traffic route choice process.