• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1998년도 추계학술대회 학술발표 논문집
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• pp.553-559
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• 1998

Simple Genetic Algorithm(SGA) proposed by J. H. Holland is a population-based optimization method based on the principle of the Darwinian natural selection. The theoretical foundations of GA are the Schema Theorem and the Building Block Hypothesis. Although GA goes well in many applications as an optimization method, still it does not guarantee the convergence to a global optimum in some problems. In designing intelligent systems, specially, since there is no deterministic solution, a heuristic trial-and error procedure is usually used to determine the systems' parameters. As an alternative scheme, therefore, there is a growing interest in a co-evolutionary system, where two populations constantly interact and co-evolve. In this paper we review the existing co-evolutionary algorithms and propose co-evolutionary schemes designing intelligent systems according to the relation between the system's components.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1998년도 추계학술대회 학술발표 논문집
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• pp.346-352
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• 1998

In this paper, we give some geometric condition for a stochastic nonlinear system and we propose a control method for a stochastic nonlinear system using neural networks. Since a competitive learning neural networks has been developed based on the stochastic approximation method, it is regarded as a stochastic recursive filter algorithm. In addition, we provide a filtering and control condition for a stochastic nonlinear system, called perfect filtering condition, in a viewpoint of stochastic geometry. The stochastic nonlinear system satisfying the perfect filtering condition is decoupled with a deterministic part and purely semi martingale part. Hence, the above system can be controlled by conventional control laws and various intelligent control laws. Computer simulation shows that the stochastic nonlinear system satisfying the perfect filtering condition is controllable. and the proposed neural controller is more efficient than the conventional LQG controller and the canoni al LQ-Neural controller.

• Computers and Concrete
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• 제13권4호
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• pp.457-482
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• 2014

This paper summarizes available literature on the optimization of reinforced concrete (RC) beams. The objective of optimization (e.g. minimum cost or weight), the design variables and the constraints considered by different studies vary widely and therefore, different optimization methods have been employed to provide the optimal design of RC beams, whether as isolated structural components or as part of a structural frame. The review of literature suggests that nonlinear deterministic approaches can be efficiently employed to provide optimal design of RC beams, given the small number of variables. This paper also presents spreadsheet implementation of cost optimization of RC beams in the familiar MS Excel environment to illustrate the efficiency of the exhaustive enumeration method for such small discrete search spaces and to promote its use by engineers and researchers. Furthermore, a sensitivity analysis is performed on the contribution of various design parameters to the variability of the overall cost of RC beams.

• 대한산업공학회지
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• 제14권2호
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• pp.11-23
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• 1988

A periodic review inventory model for deteriorating items in which time is treated as a discrete variable is developed. The model is developed under deterministic but time dependent demands and instantaneous delivery. Deterioration is assumed to be a constant fraction of the on hand inventory and partial returns are allowed for the deteriorated items. The solution procedures for obtaining the optimal order quantities which maximize the total profit in the scheduling period are presented for the cases of back orders and lost sales. Finally, when the additional orders are allowed, an efficient solution algorithm determining the initial and additional order quantities and additional ordering time is developed. Some numerical examples are also presented to illustrate the results.

• 대한의용생체공학회:학술대회논문집
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• 대한의용생체공학회 1996년도 춘계학술대회
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• pp.27-30
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• 1996

PR interval variability has been proposed as a noninvasive tool for in-vestigating the autonomic nervous system as welt as heart rate variability. The goal of this paper is to determine whether PR interval variability is generated from deterministic nonlinear dynamics. The data used in this study is a 24-hour bolter ECGs of 20 healthy adults. We developed an automatic PR interval measurement algorithm, and tested it using MIT ECG Databases. The general discriminants of nonlinear dynamics, such as, correlation dimension and phase space reconstruction are used. Surrogate data is generated from simpler linear models to have similar statistical characteristics with the original data. Nonlinear discriminants are applied to both data, and compared for any significant results. It was concluded that PR interval variability shows non-linear characteristics.

• 대한산업공학회지
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• 제16권1호
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• pp.51-58
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• 1990

A deterministic capacity expansion planning model for a two-capacity type facility is analyzed to determine the sizes to be expanded in each period so as to supply the known demands for two distinct capacity type(product) on time and to minimize the total cost incurred over a finite planning horizon of T periods. The model assumes that capacity unit of the facility simultaneously serves a prespecified number of demand units of each capacity type, that capacity type 1 can be used to supply demands for capacity type 2, but that capacity type 2 can't be used to supply demands for capacity type 1. Capacity expansion and excess capacity holding cost functions considered are nondecreasing and concave. The structure of an optimal solution is characterized and then used in developing an efficient dynamic programming algorithm that finds optimal capacity planning policy.

• Industrial Engineering and Management Systems
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• 제11권1호
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• pp.18-25
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• 2012

IChinese postman problem is one of the classical combinatorial optimization problems with many applications. However, in application, some uncertain factors are frequently encountered. This paper employs uncertain programming to deal with Chinese postman problem with uncertain weight Within the framework of uncertainty theory, the concepts of expected shortest route, ${\alpha}$-shortest route, and distribution shortest route are proposed. After that, expected shortest model, and ${\alpha}$-shortest model are constructed. Taking advantage of properties of uncertainty theory, these models can be transf-ormed into their corresponding deterministic forms, which can be solved by classical algorithm..

• 한국정보보호학회:학술대회논문집
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• 한국정보보호학회 2003년도 동계학술대회
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• pp.299-306
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• 2003

본 논문에서는 현재 사용되고 있는 소수성 검정 알고리즘의 효율성을 비교하여 효과적인 알고리즘 사용에 관한 방향을 제시하려 한다. 현재 가장 일반적으로 사용하고 있는 Miller-Rabin 소수성검정법(Miller-Rabin primality test)에 대하여, Miller-Rabin 소수성 검정법 이외에 다른 확률적 소수성 검정법으로 제안된 Frobenius-Grantham 소수성 검정법(Frobenius-Grantham primality test) 이 있다. 그러나 합성수 판별에 대한 확률적 우세함에도 불구하고, Miller-Rabin 소수성 검정법을 대체하고 있지 못하는 이유는 시간복잡도(time complexity)가 Randomized polynomial time이기 때문에 같은 확률에 대한 평균 실행 속도가 Miller-Rabin 소수성 검정법보다 크게 효율적이지 못하기 때문이다. 또한, 2002년 Manindra Agrawal이 제시한 AKS 알고리즘(AKS algorithm)은 최초의 다항식 시간내 결정적 소수성 검정법(Polynomial time deterministic primality test)이지만, 시간 복잡도에서 다항식의 차수가 높기 때문에 현재 사용되고 있는 확률적 소수성 검정법(Probabilistic primality test)을 대체하지 못할 것으로 사료된다. 본 논문에서는 최근 발표된 소수성 검정법인 Frobenius-Grantham 소수성 검정법, AKS 알고리즘과 기존의 Miller-Rabin 소수성 검정법의 장단점을 비교·분석해 보고자 한다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2003년도 학술회의 논문집 정보 및 제어부문 B
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• pp.998-1001
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• 2003

In this paper, a entertainment biped robot controlled by R/C servo motors is built using the embedded RTOS (Real Time Operating System). uC/OS-II V2.00 is used for RTOS and control algorithm of R/C servo motors is proposed based on uC/OS-II's preemptive and deterministic property without any extra PWM module. The realized biped robot has 19 DOF, and a board 80C196KC as main CPU. To verify the proper walking process, ZMP(Zero Moment Point) theory is applied and ADAMS is used for simulation.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1993년도 하계학술대회 논문집 B
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• pp.932-934
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• 1993

Optimum pole shape is designed to increase the levitation and propulsion force of magnetic levitation systems. Evolution Strategy is introduced as optimization method. Evolution Strategy is random based non-deterministic method, developed by combining Genetic Algorithm with Simulated Annealing. Trasnsrapid-06, which was developed in Germany, is referenced model to be analyze. Design variables are nodes which determine fields pole shape of a linear synchronous motor, and the model analyzed by F.E.M.