• Transactions of the Korean Society of Mechanical Engineers A
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• v.28 no.9
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• pp.1399-1407
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• 2004

Structural optimization has been carried out in continuous design space or in discrete design space. Generally, available designs are discrete in design practice. However, the methods for discrete variables are extremely expensive in computational cost. An iterative optimization algorithm is proposed for design in a discrete space, which is called a sequential algorithm using orthogonal arrays (SOA). We demonstrate verifying the fact that a local optimum solution can be obtained from the process with this algorithm. The local optimum solution is defined in a discrete design space. Then the search space, which is a set of candidate values of each design variables formed by the neighborhood of a current design point, is defined. It is verified that a local optimum solution can be found by sequentially moving the search space. The SOA algorithm has been applied to problems such as truss type structures. Then it is confirmed that a local solution can be obtained by using the SOA algorithm

• Proceedings of the KSME Conference
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• 2004.04a
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• pp.1005-1010
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• 2004

The structural optimization has been carried out in the continuous design space or in the discrete design space. Generally, available designs are discrete in design practice. But methods for discrete variables are extremely expensive in computational cost. In order to overcome this weakness, an iterative optimization algorithm was proposed for design in the discrete space, which is called as a sequential algorithm using orthogonal arrays (SOA). We focus to verify the fact that the local solution can be obtained throughout the optimization with this algorithm. The local solution is defined in discrete design space. Then the search space, which is the set of candidate values of each design variables formed by the neighborhood of current design point, is defined. It is verified that a local solution can be founded by moving sequentially the search space. The SOA algorithm has been applied to problems such as truss type structures. Then it is confirmed that a local solution can be obtained using the SOA algorithm

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.16 no.4
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• pp.270-275
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• 2016

We present an approach for acceleration actor-critic algorithm for reinforcement learning with continuous action space. Actor-critic algorithm has already proved its robustness to the infinitely large action spaces in various high dimensional environments. Despite that success, the main problem of the actor-critic algorithm remains the same-speed of convergence to the optimal policy. In high dimensional state and action space, a searching for the correct action in each state takes enormously long time. Therefore, in this paper we suggest a search accelerating function that allows to leverage speed of algorithm convergence and reach optimal policy faster. In our method, we assume that actions may have their own distribution of preference, that independent on the state. Since in the beginning of learning agent act randomly in the environment, it would be more efficient if actions were taken according to the some heuristic function. We demonstrate that heuristically-accelerated actor-critic algorithm learns optimal policy faster, using Educational Process Mining dataset with records of students' course learning process and their grades.

• Spatial Information Research
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• v.18 no.1
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• pp.77-87
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• 2010

Spatio-temporal join operators are essential to the management of spatio-temporal data such as moving objects. For example, the join operators are parts of processing to analyze movement of objects and search similar patterns of moving objects. Various studies on spatio-temporal join queries in outdoor space have been done. Recently with advance of indoor positioning techniques, location based services are required in indoor space as well as outdoor space. Nevertheless there is no one about processing of spatio-temporal join query in indoor space. In this paper, we introduce continuous spatio-temporal self-join queries in indoor space and propose a method of processing of the join queries over stream data of moving objects. The continuous spatio-temporal self-join query is to update the joined result set satisfying spatio-temporal predicates continuously. We assume that positions of moving objects are represented by symbols such as a room or corridor. This paper proposes a data structure, called Candidate Pairs Buffer, to filter and maintain massive stream data efficiently and we also investigate performance of proposed method in experimental study.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.5 s.176
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• pp.1193-1202
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• 2000

The paper describes the use of genetic algorithms (GA's) to the minimum weight design of stiffened composite panels for buckling constraints. The proposed design problem is characterized by mixture of continuous and discrete design variables corresponding to panel elements and stacking sequence of laminates, respectively. Design space is multimodal and non-convex, thereby introducing the need for global search strategies. Advanced strategies in GA's such as directed crossover, multistage search and separated crossover are adopted to improve search ability and to save computational resource requirements. The paper explores the effectiveness of genetic algorithms and their advanced strategies in designing stiffened composite panels under various uniaxial compressive load conditions and the linrlit on stacking sequence of laminates.

• The Journal of the Korea Contents Association
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• v.20 no.11
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• pp.636-643
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• 2020

The differential evolution algorithm is one of the meta-heuristic techniques developed to solve the real optimization problem, which is a continuous problem space. In this study, in order to use the differential evolution algorithm to solve the traveling salesman problem, which is a discontinuous problem space, a random key representation method is applied to the differential evolution algorithm. The differential evolution algorithm searches for a real space and uses the order of the indexes of the solutions sorted in ascending order as the order of city visits to find the fitness. As a result of experimentation by applying it to the benchmark traveling salesman problems which are provided in TSPLIB, it was confirmed that the proposed differential evolution algorithm based on the random key representation method has the potential to solve the traveling salesman problems.

• Journal of KIISE:Computer Systems and Theory
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• v.26 no.9
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• pp.1166-1176
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• 1999

연속 매체, 특히 비디오 데이타에 대한 일반 사용자 연산에는 재생뿐만 아니라 임의 속도 탐색 연산, 정지 연산, 그리고 그 외 다양한 연산이 있다. 이 연산 중에서 원하는 화면을 빨리 찾는 데에 유용한 고속 전진(FF: fast-forward)과 고속 후진(FB: fast-backward)은 재생 연산과는 달리 비순차적인 디스크 접근을 요구한다. 이러한 경우에 디스크 부하가 균등하지 않으면 일부 디스크에 접근이 편중되어 서비스 품질이 떨어진다. 본 논문에서는 디스크 배열을 이용한 저장 시스템에서 디스크 접근을 고르게 분산시키기 위하여 '소수 라운드 로빈(PRR: Prime Round Robin)' 방식으로 연속 매체를 디스크에 배치하는 기법에서 문제가 됐던 낭비된 디스크 저장 공간을 신뢰도 향상을 위해서 사용하는 '그룹화된 패리티를 갖는 소수 라운드 로빈(PRRgp: PRR with Grouped Parities)' 방식을 제안한다. 이 기법은 PRR 기법처럼 임의 속도 검색 연산에 있어서 디스크 배열을 구성하는 모든 디스크의 부하를 균등하게 할뿐만 아니라 낭비됐던 디스크 저장 공간에 신뢰도를 높이기 위한 패리티 정보를 저장함으로서 신뢰도를 향상시킬 수 있다. 신뢰도 모델링 방법으로 조합 모델과 마르코프 모델을 이용해서 결함발생율과 결함복구율을 고려한 신뢰도를 산출하고 비교.분석한다. PRR 기법으로 연속 매체를 저장하고 낭비되는 공간에 패리티 정보를 저장할 경우에 동시에 두 개 이상의 결함 발생 시에 그 결함으로부터 복구가 불가능하지만 PRRgp 기법에서는 약 30% 이상의경우에 대해서 동시에 두 개의 결함 발생 시에 저장한 패리티 정보를 이용한 복구가 가능할 뿐만 아니라 패리티 그룹의 수가 두 개 이상인 경우에는 두 개 이상의 결함에 대해서도 복구가 가능하다.Abstract End-user operations on continuous media (say video data) consist of arbitrary-rate search, pause, and others as well as normal-rate play. FF(fast-forward) / FB(fast-backward) among those operations are desirable to find out the scene of interest but they require non-sequential access of disks. When accesses are clustered to several disks without considering load balance, high quality services in playback may not be available. In this paper, we propose a new disk placement scheme, called PRRgp(Prime Round Robin with Grouped Parities), with enhanced reliability by using the wasted disk storage space in an old one(PRR: Prime Round Robin), in which continuous media are placed on a disk array based storage systems to distribute disk accesses uniformly. The PRRgp can not only achieve load balance of disks consisting of a disk array under arbitrary-rate search like PRR, but also improve reliability by storing parity information on the wasted disk space appropriately. We use combinatorial and Markov models to evaluate the reliability for a disk array and to analyze the results. When continuous media like PRR are placed and parity information on the wasted disk space is stored, we cannot tolerate more than two simultaneous faults. But they can be recovered by using stored parity information for about 30 percent as a whole in case of PRRgp presented in this paper. In addition, more than two faults can be tolerated in case there are more than two parity groups.

• Journal of Mechanical Science and Technology
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• v.16 no.4
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• pp.454-467
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• 2002

It has been established that a crack has an important effect on the dynamic behavior of a structure. This effect depends mainly on the location and depth of the crack. Toidentifythelocation and depth of a crack in a structure, a method is presented in this paper which uses neuro-fuzzy-evolutionary technique, that is, Adaptive-Network-based Fuzzy Inference System (ANFIS) solved via hybrid learning algorithm (the back-propagation gradient descent and the least-squares method) and Continuous Evolutionary Algorithms (CEAs) solving sir ale objective optimization problems with a continuous function and continuous search space efficiently are unified. With this ANFIS and CEAs, it is possible to formulate the inverse problem. ANFIS is used to obtain the input(the location and depth of a crack) - output(the structural Eigenfrequencies) relation of the structural system. CEAs are used to identify the crack location and depth by minimizing the difference from the measured frequencies. We have tried this new idea on beam structures and the results are promising.

• MALSORI
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• no.64
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• pp.137-153
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• 2007

The pronunciation lexicon of a continuous speech recognition system should contain enough pronunciation variations to be used for building a search space large enough to contain a correct path, whereas the size of the pronunciation lexicon needs to be constrained for effective decoding and lower perplexities. This paper describes a procedure for selecting pronunciation variations to be included in the lexicon based on the frequencies of the corresponding phonetic rules observed in the training corpus. Likelihood of a phonetic rule's application is estimated using the observation frequency of the rule and is used to control the construction of a pronunciation lexicon. Experiments with various pronunciation lexica show that the proposed method is helpful to improve the speech recognition performance.

• Journal of KIISE:Databases
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• v.28 no.4
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• pp.655-664
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• 2001

The continuous data such as video streams and voice analog signals can be modeled as multidimensional data sequences(MDS's) in the feature space, In this paper, we investigate the clustering technique for multidimensional data sequence, Each sequence is represented by a small number by hyper rectangular clusters for subsequent storage and similarity search processing. We present a linear clustering algorithm that guarantees a predefined level of clustering quality and show its effectiveness via experiments on various video data sets.