• Journal of applied mathematics & informatics
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• 제3권1호
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• pp.11-24
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• 1996

The focus of this research is the class of sequential al-gorithms called predictive sorting algorithms for sorting a given set of n elements using pairwise comparisons. The order in which these pairwise comparisons are made is defined by a fixed sequence of all un-ordered pairs of distinct integers{1,2 ···,n} called a sort sequence. A predictive sorting algorithm associated with a sort sequence spec-ifies pairwise comparisons of elements in the input set in the order defined by the sort sequence except that the comparisons whose out-comes can be inferred from the preceding pairs of comparisons are not performed. in this paper predictive sorting algorithms are obtained based on known sorting algorithms and are shown to be required on the average O(n log n) comparisons.

• 디지털산업정보학회논문지
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• 제8권2호
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• pp.11-19
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• 2012

Crane systems have been widely used for transportation in building sites, ports, nuclear wastehandling operation and so on. As a typical underactuated system, an overhead crane has such merits as high flexibility and less energy consumption. And it's getting more types of cranes, universally applicable algorithms should be developed. That is the design and development of scalable algorithms are required. Developed algorithms can be used for the controller and crane overload protection that meets the requirements of the algorithm are presented. These algorithms force the state to warn the operator and stops the operation of equipment. In this paper, crane overload conditions that can cause damage to alert the operator, and to limit the operation of equipment overload protection algorithm is presented.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2001년도 Proceedings ICPE 01 2001 International Conference on Power Electronics
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• pp.746-750
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• 2001

During the last decades several proposals have been made in literature to use predictive control for inverter control-especially in electrical drives. These algorithms are completely different to the recursive but linear predictive algorithms known from information theory, where closed mathematical equations are used (e.g. Kalman-filters). Only few of the presented schemes have been realized in industrial applications so far. After some further progress, however, the advantage of predictive algorithms might lead to an increased number of industrial implementations in the future. Besides the common basic idea - to use the well-known but strongly non-linear behaviour of inverters to precalculate the best switching times - there are many differences in the details of these proposals. This contribution shows similarities and differences and attempts to design a 'family tree' of predictive control algorithms. This might grow to a first step to a theoretical approach to deal with predictive control schemes in a more generalised way.

• 공학교육연구
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• 제15권4호
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• pp.41-47
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• 2012

Data mining and knowledge discovery techniques have shown to be effective in finding hidden underlying rules inside large database in an automated fashion. On the other hand, analyzing, assessing, and applying students' survey data are very important in science and engineering education because of various reasons such as quality improvement, engineering design process, innovative education, etc. Among those surveys, analyzing the students' views on science-technology-society can be helpful to engineering education. Because, although most researches on the philosophy of science have shown that science is one of the most difficult concepts to define precisely, it is still important to have an eye on science, pseudo-science, and scientific misconducts. In this paper, we report the experimental results of applying decision tree induction algorithms for analyzing the questionnaire results of high school students' views on science-technology-society (HS-VOSTS). Empirical results on various settings of decision tree induction on HS-VOSTS results from one South Korean university students indicate that decision tree induction algorithms can be successfully and effectively applied to automated knowledge discovery from students' survey data.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.140-140
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• 2000

Traditional genetic algorithms, though robust, are generally not the most successful optimization algorithm on any particular domain. Hybridizing a genetic algorithm with other algorithms can produce better performance than both the genetic algorithm and the other algorithms. In this paper, we use random process and simulated annealing instead of mutation operator in order to get well tuned fuzzy rules. The key of this approach is to adjust both the width and the center of membership functions so that the tuned rule-based fuzzy controller can generate the desired performance. The effectiveness of the proposed algorithm is verified by computer simulation.

• 수산해양교육연구
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• 제24권4호
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• pp.528-542
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• 2012

In this study, we designed and applied the learning program of various algorithms about computer science, which were based on computational thinking, to prospective elementary school teachers who were non-majors of this field. While they were learning, they could understand two fundamental functions of computational thinking: abstraction and automation. This learning program made them change their perceptions about computer science positively. They had been interested in learning algorithms and computer science itself, and they felt confident about teaching it.

• 전기학회논문지
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• 제59권5호
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• pp.972-980
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• 2010

In this study, we introduce the design methodology of an optimized type-2 fuzzy cascade controller with the aid of hierarchical fair competition-based genetic algorithm(HFCGA) for ball & beam system. The ball & beam system consists of servo motor, beam and ball, and remains mutually connected in line in itself. The ball & beam system determines the position of ball through the control of a servo motor. Consequently the displacement change of the position of the moving ball and its ensuing change of the angle of the beam results in the change of the position angle of a servo motor. The type-2 fuzzy cascade controller scheme consists of the outer controller and the inner controller as two cascaded fuzzy controllers. In type-2 fuzzy logic controller(FLC) as the expanded type of type-1 fuzzy logic controller(FLC), we can effectively improve the control characteristic by using the footprint of uncertainty(FOU) of membership function. The control parameters(scaling factors) of each fuzzy controller using HFCGA which is a kind of parallel genetic algorithms(PGAs). HFCGA helps alleviate the premature convergence being generated in conventional genetic algorithms(GAs). We estimated controller characteristic parameters of optimized type-2 fuzzy cascade controller applied ball & beam system such as maximum overshoot, delay time, rise time, settling time and steady-state error. For a detailed comparative analysis from the viewpoint of the performance results and the design methodology, the proposed method for the ball & beam system which is realized by the fuzzy cascade controller based on HFCGA, is presented in comparison with the conventional PD cascade controller based on serial genetic algorithms.

• 제어로봇시스템학회논문지
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• 제8권12호
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• pp.1041-1047
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• 2002

It is known that parallel-type mechanisms have many singularities than serial-type mechanisms. In haptic application, these singularities deteriorate the system performance when the haptic system displays the reflecting force. Moreover, different from general manipulators, haptic systems can't avoid the singular point because they are operated by user's random motion command. Although many singularity-free algorithms for serial mechanisms have been proposed and studied. singularity-free algorithms for parallel haptic application have not been deeply discussed. In this paper, various singularity-free algorithms, which are appropriate to parallel haptic system, will be discussedand evaluated.

• 생물환경조절학회지
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• 제7권4호
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• pp.290-297
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• 1998

겨울철 온실의 기본적인 열에너지원인 일사를 최대한 확보하도록 하는 은실의 지붕형상을 결정하기 위해 유전알고리즘 및 광투과율 전산모델을 이용한 최적화기법을 이용하여 설치지역, 피복재료특성, 온실의 기본치수등이 주어졌을 때 지붕경사각, 경간폭비의 최적조합을 결정할 수 있도록 하는 최적설계를 수행하였다. 수원지방에 위치한 경간폭 6m의 2연동 동서동 온실 및 단동 온실을 가정하여 최적화를 수행한 결과 경사각, 폭비 순으로 2연동, 단동 온실에 대해 각각 40.861≒40 $_。 / , 0.4806≒0.5, 37.490≒37 $_。 / , 0.7748≒0.78의 결과를 얻을 수 있었다. 광투과율 문제를 예로 적용해 본 결과 직접 전산모델을 호출하여 최적화를 수행하는 유전알고리즘의 기법은 온실환경의 해석을 위해 연구되어온 다양한 분야의 전산모델들을 종합적인 온실의 최적설계에 활용하도록 하는데 유용한 기법이 될 것으로 판단되었다.판단되었다.

• 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.