• 한국정보전자통신기술학회논문지
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• 제16권4호
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• pp.203-209
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• 2023

Harmony search(HS)는 새로운 하모니를 구성할 때 HM을 참조하는 경우 개별 하모니의 평가를 이용하지 않지만 PSO(particle swarm optimization)는 개별 입자의 평가와 모집단의 평가를 이용하여 해를 찾아간다. 그러나 본 연구에서는 HS와 PSO의 유사점을 찾아 PSO의 입자 개선 과정을 HS에 적용하여 알고리즘의 성능을 향상시키고자 하였다. PSO 알고리즘을 적용하기 위해서는 개별 입자의 local best와 떼(swam)의 global best가 필요하다. 본 연구에서는 HS가 harmony memory(HM)에서 가장 나쁜 하모니을 개선하는 과정을 PSO와 매우 유사한 과정으로 보았다. 이에 따라 HM의 가장 나쁜 하모니를 입자의 PSO의 local best로, 가장 좋은 하모니는 PSO의 global best 최고로 간주하였다. 이와 같이 PSO의 입자 개선과정을 HS 하모니 개선과정에 도입하여 HS의 성능을 향상시킬 수 있었다. 본 연구의 결과는 다양한 함수에 대한 최적화 예시를 통해 비교 확인하였다. 그 결과 정확성과 일관성에 있어 기존 HS보다 제안한 HS-PSO가 매우 우수함을 알 수 있었다.

• Structural Engineering and Mechanics
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• 제42권6호
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• pp.783-797
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• 2012

A new hybrid meta-heuristic optimization algorithm is presented for design of structures. The algorithm is based on the concepts of the charged system search (CSS) and the particle swarm optimization (PSO) algorithms. The CSS is inspired by the Coulomb and Gauss's laws of electrostatics in physics, the governing laws of motion from the Newtonian mechanics, and the PSO is based on the swarm intelligence and utilizes the information of the best fitness historically achieved by the particles (local best) and by the best among all the particles (global best). In the new hybrid algorithm, each agent is affected by local and global best positions stored in the charged memory considering the governing laws of electrical physics. Three different types of structures are optimized as the numerical examples with the new algorithm. Comparison of the results of the hybrid algorithm with those of other meta-heuristic algorithms proves the robustness of the new algorithm.

• 대한전기학회논문지:전력기술부문A
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• 제48권3호
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• pp.313-320
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• 1999

The Lane-Curvature Method(LCM) presented in this paper is a new local obstacle avoidance method for indoor mobile robots. The method combines Curvature-Velocith Method(CVM) with a new directional method called the Lane Method. The Lane Method divides the environment into lanes taking the information on obstacles and desired heading of the robot into account ; then it chooses the best lane to follow to optimize travel along a desired heading. A local heading is then calculated for entering and following the best lane, and CVM uses this heading to determine the optimal translational and rotational velocity space methods, LCM yields safe collision-free motion as well as smooth motion taking the dynamics of the robot Xavier, show the efficiency of the proposed method.

• 한국언어정보학회:학술대회논문집
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• 한국언어정보학회 2007년도 정기학술대회
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• pp.303-310
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• 2007

Named Entity Recognition (NER) is always limited by its lower recall resulting from the asymmetric data distribution where the NONE class dominates the entity classes. This paper presents an approach that exploits non-local information to improve the NER recall. Several kinds of non-local features encoding entity token occurrence, entity boundary and entity class are explored under Conditional Random Fields (CRFs) framework. Experiments on SIGHAN 2006 MSRA (CityU) corpus indicate that non-local features can effectively enhance the recall of the state-of-the-art NER systems. Incorporating the non-local features into the NER systems using local features alone, our best system achieves a 23.56% (25.26%) relative error reduction on the recall and 17.10% (11.36%) relative error reduction on the F1 score; the improved F1 score 89.38% (90.09%) is significantly superior to the best NER system with F1 of 86.51% (89.03%) participated in the closed track.

• Journal of Mechanical Science and Technology
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• 제17권11호
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• pp.1693-1703
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• 2003

This paper presents a new local obstacle avoidance method for indoor mobile robots. The method uses a new directional approach called the Lane Method. The Lane Method is combined with a velocity space method i.e., the Curvature-Velocity Method to form the Lane-Curvature Method (LCM). The Lane Method divides the work area into lanes, and then chooses the best lane to follow to optimize travel along a desired goal heading. A local heading is then calculated for entering and following the best lane, and CVM uses this local heading to determine the optimal translational and rotational velocities, considering some physical limitations and environmental constraint. By combining both the directional and velocity space methods, LCM yields safe collision-free motion as well as smooth motion taking the physical limitations of the robot motion into account.

• 한국컴퓨터정보학회논문지
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• 제23권12호
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• pp.1-9
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• 2018

The multiple-choice multidimensional knapsack problem (MMKP) is a variant of the well known 0-1 knapsack problem, which is known as an NP-hard problem. This paper proposes a method for solving the MMKP using the integer programming-based local search (IPbLS). IPbLS is a kind of a local search and uses integer programming to generate a neighbor solution. The most important thing in IPbLS is the way to select items participating in the next integer programming step. In this paper, three ways to select items are introduced and compared on 37 well-known benchmark data instances. Experimental results shows that the method using linear programming is the best for the MMKP. It also shows that the proposed method can find the equal or better solutions than the best known solutions in 23 data instances, and the new better solutions in 13 instances.

• Journal of Multimedia Information System
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• 제4권2호
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• pp.89-92
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• 2017

This paper investigates simple gray level image enhancement technique based on Genetic Algorithms and Local Statistics. The task of GA is to adapt the parameters of local sliding masks over pixels, finding out the best parameters preserving the brightness and possibly preventing the creation of intensity artifacts in the local area of images. The algorithm is controlled by GA as to enhance the contrast and details in the images automatically according to an object fitness criterion. Results obtained in terms of subjective and objective evaluations, show the plausibility of the method suggested here.

• 대한전기학회논문지:전력기술부문A
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• 제53권10호
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• pp.565-572
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• 2004

This paper proposes an expert system which can enhance the accuracy of real-time bus reconfiguration strategy by adopting local minimum tree search method and minimize the spreading effect of the fault by considering totally the operating condition when a main transformer fault occurs in the automated substation. The local minimum tree search method to expand the best-first search method. This method has an advantage which can improve the performance of solution within the limits of the real-time condition. The inference strategy proposed expert system consists of two stages. The first stage determines the switching candidate set by searching possible switching candidates starting from the main transformer or busbar related to the event. And, second stage determines the rational real-time bus reconfiguration strategy based on heuristic rules for the obtained switching candidate set. Also, this paper studies the generalized distribution substation modelling using graph theory and a substation database is designed based on the study result. The inference engine of the expert system and the substation database 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 local minimum tree search solution based on diversity event simulations for typical distribution substation.

• 산업경영시스템학회지
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• 제20권42호
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• pp.39-47
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• 1997

There are four parameters (i.e. overall density, local density, grouping, layout complexity) to consider in designing screen of a visual display terminal. Among these, only the optimum level of overall density is known to be about 25~30% by some studies. Therefore, the present experiment is conducted to define the optimum levels of the other parameters to achieve the user's best performance in visual search task. The results are as follows; (1) The function related to the levels of local density and user's search times is shown to be U -shaped. When the level of local density is about 40%, the search time is shorter than those of any other levels. (2) In the experiment of grouping, user's performance is best when the number of group is 5, and the size of group does not exceed visual angle $5^{\circ}$ (0,088rad). (3) The user performance is improved as the layout becomes less complex.

• Communications for Statistical Applications and Methods
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• 제29권3호
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• pp.353-371
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• 2022

This paper analyzes death counts after World War II of several countries to identify and to compare their stochastic structures. The stochastic structures that this paper entertains are three structural time series models, a local level with a random walk model, a fixed local linear trend model and a local linear trend model. The structural time series models assume that a time series can be formulated directly with the unobserved components such as trend, slope, seasonal, cycle and daily effect. Random effect of each unobserved component is characterized by its own stochastic structure and a distribution of its irregular component. The structural time series models use the Kalman filter to estimate unknown parameters of a stochastic model, to predict future data, and to do filtering data. This paper identifies the best-fitted stochastic model for three types of death counts (Female, Male and Total) of each country. Two diagnostic procedures are used to check the validity of fitted models. Three criteria, AIC, BIC and SSPE are used to select the best-fitted valid stochastic model for each type of death counts of each country.