• 통합자연과학논문집
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• 제14권3호
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• pp.73-77
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• 2021

Robust design is an approach to reduce the performance variation of mutiple responses in products and processes. In fact, in many experimental designs require the simultaneous optimization of multiple responses. In this paper, we propose how to simultaneously optimize multiple responses for robust design when data are collected from a combined array. The proposed method is based on the quadratic loss function. An example is illustrated to show the proposed method.

• 통합자연과학논문집
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• 제12권3호
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• pp.69-73
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• 2019

Taguchi has used the signal-to-noise ratio (SN) to achieve the appropriate set of operating conditions where variability around target is low in the Taguchi parameter design. Taguchi has dealt with having constraints on both the mean and variability of a characteristic (the dual response problem) by combining information on both mean and variability into an SN. Many Statisticians criticize the Taguchi techniques of analysis, particularly those based on the SN. In this paper we propose a substantially simpler optimization procedure for parameter design to solve the dual response problems without resorting to SN.

• 대한기계학회논문집A
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• 제29권9호
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• pp.1243-1252
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• 2005

A current trend of design methodologies is to make engineers objectify or automate the decision-making process. Numerical optimization is an example of such technologies. However, in numerical optimization, the uncertainties are uncontrollable to efficiently objectify or automate the process. To better manage these uncertainties, the Taguchi method, reliability-based optimization and robust optimization are being used. To obtain the target performance with the maximum robustness is the main functional requirement of a mechanical system. In this research, a design procedure for global robust optimization is developed based on the kriging and global optimization approaches. The DACE modeling, known as the one of Kriging interpolation, is introduced to obtain the surrogate approximation model of the function. Robustness is determined by the DACE model to reduce real function calculations. The simulated annealing algorithm of global optimization methods is adopted to determine the global robust design of a surrogated model. As the postprocess, the first order second-moment approximation method is applied to refine the robust optimum. The mathematical problems and the MEMS design problem are investigated to show the validity of the proposed method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권11호
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• pp.4268-4289
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• 2020

Advanced traffic signal timing method plays very important role in reducing road congestion and air pollution. Reinforcement learning is considered as superior approach to build traffic light timing scheme by many recent studies. It fulfills real adaptive control by the means of taking real-time traffic information as state, and adjusting traffic light scheme as action. However, existing works behave inefficient in complex intersections and they are lack of feasibility because most of them adopt traffic light scheme whose phase sequence is flexible. To address these issues, a novel adaptive traffic signal timing scheme is proposed. It's based on actor-critic reinforcement learning algorithm, and advanced techniques proximal policy optimization and generalized advantage estimation are integrated. In particular, a new kind of reward function and a simplified form of state representation are carefully defined, and they facilitate to improve the learning efficiency and reduce the computational complexity, respectively. Meanwhile, a fixed phase sequence signal scheme is derived, and constraint on the variations of successive phase durations is introduced, which enhances its feasibility and robustness in field applications. The proposed scheme is verified through field-data-based experiments in both medium and high traffic density scenarios. Simulation results exhibit remarkable improvement in traffic performance as well as the learning efficiency comparing with the existing reinforcement learning-based methods such as 3DQN and DDQN.

• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2010년도 한국컴퓨터종합학술대회논문집 Vol.37 No.1(A)
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• pp.146-147
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• 2010

• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2007년도 한국컴퓨터종합학술대회논문집 Vol.34 No.1 (A)
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• pp.7-8
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• 2007

• Journal of Pharmaceutical Investigation
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• 제21권1호
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• pp.23-32
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• 1991

Dissolution profiles of ketoconazole in solid dispersion system (SDS) were investigated in the second fluid (pH 6.8) for the dissolution test (KPV). PVP K-30 and methyl cellulose were used as carriers in SDS, and chloroform as a solvent. Computer optimization technique was applied to obtain an optimum formula of SDS, and the following results were obtained; 1) Dissolution rate of ketoconazole in SDS was larger than that of pure ketoconazole in the second fluid of pH 6.8. 2) PVP K-30 and methyl cellulosr were good carriers for SDS of ketoconazole. Moerover PVP K-30 was better than methyl cellulose. 3) The optimum formula of ketoconazole SDS obtained from computer optimization technique was chloroform 175 ml, PVP K-30 5g and methyl cellulose 0.2g per 1g of ketoconazole. 4) The experimental value of $A_{60}$ (Amount released from ketoconazole tablet during 60 minutes) obtained from SDS by optimum formula agreed well with the value calculated by polynomial regression equation.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.324-329
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• 2005

Dynamic Encoding Algorithm for Searches (DEAS) which is known as a fast and reliable non-gradient optimization method, was proposed [1]. DEAS reaches local or global optimum with binary strings (or binary matrices for multi-dimensional problem) by iterating the two operations; bisectional search (BSS) and unidirectional search (UDS). BSS increases binary strings by one digit (i.e., 0 or 1), while UDS performs increment or decrement of binary strings in the BSS' result direction with no change of string length. Because the interval of UDS exponentially decreases with increment of bit string length (BSL), DEAS is difficult to escape from local optimum when DEAS falls into local optimum. Therefore, this paper proposes hopping UDS (HUDS) which performs UDS by hopping as many as BSL in the final point of UDS process. HUDS helps to escape from local optimum and enhances a probability searching global optimization. The excellent performance of HUDS will be validated through the well-known benchmark functions.

• 한국해양공학회지
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• 제23권1호
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• pp.48-53
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• 2009

Autonomous Underwater Vehicles (AUV's) provide an important means for collecting detailed scientific information from the ocean depths. The hull resistance of an AUV is an important factor in determining the power requirements and range of the vehicle. This paper describes a design method that uses Computational Fluid Dynamics (CFD) to determine the hull resistance of an AUV under development. The CFD results reveal the distribution of the hydrodynamic values (velocity, pressure, etc.) of an AUV with a ducted propeller. This paper also discusses the optimization of the AUV hull profile to reduce the total resistance. This paper demonstrates that shape optimization in a conceptual design is possible by using a commercial CFD package. Optimum design work to minimize the drag force of an AUV was carried out, for a given object function and constraints.

• 대한기계학회논문집
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• 제14권3호
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• pp.594-602
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• 1990

본 연구에서는 동력전달용 인벌류우트 원통치차(스퍼어 및 헬리컬 기어)의 강 도 및 각종 영향인자를 충분히 고려하면서 크기를 최소로 하는 치차장치의 설계법을 개발하고, 이 설계법을 기본으로 하여 퍼스널 컴퓨터 상에서 누구나 손쉽게 설계에 이 용할 수 있는 설계 시스템을 개발하여 그 평가를 수행한다.