• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2002년도 춘계학술대회 논문집
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• pp.450-453
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• 2002

This paper is concerned with smooth walking robot using genetic algorithm. The new walking algorithm is proposed and we simulated and experimented the algorithm. We suggested the leg trajectory algorithm and balancing trajectory algorithm by applying genetic algorithm. First the leg trajectory algorithm generated the smooth trajectory. Also the balancing trajectory generated the optimal trajectory. We compared results with the previous walking algorithm. It showed that the new proposed algorithm generated the better walking trajectory.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제6권10호
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• pp.2509-2528
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• 2012

Time division multiple access (TDMA) is a widely used media access control (MAC) technique that can provide collision-free and reliable communications, save energy and bound the delay of packets. In TDMA, energy saving is usually achieved by switching the nodes' radio off when such nodes are not engaged. However, the frequent switching of the radio's state not only wastes energy, but also increases end-to-end delay. To achieve high energy efficiency and low delay, as well as to further minimize the number of time slots, a multi-objective TDMA scheduling problem for industrial wireless mesh networks is presented. A hybrid algorithm that combines genetic algorithm (GA) and simulated annealing (SA) algorithm is then proposed to solve the TDMA scheduling problem effectively. A number of critical techniques are also adopted to reduce energy consumption and to shorten end-to-end delay further. Simulation results with different kinds of networks demonstrate that the proposed algorithm outperforms traditional scheduling algorithms in terms of addressing the problems of energy consumption and end-to-end delay, thus satisfying the demands of industrial wireless mesh networks.

• 한국ITS학회 논문지
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• 제5권2호
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• pp.11-18
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• 2006

본 논문에서는 Non-ideal한 수신단 필터에 들어오는 간섭양을 계산하는 알고리즘을 제시하였으며, 또한 간섭양 계산 시보다 빠르게 계산 할 수 있는 방법도 설명하였다. 본 논문에서 설명된 알고리즘은 Matlab을 이용하여 시뮬레이션 하였으며 시뮬레이션 방법은 순서도를 사용하여 설명하였다. 알고리즘의 검증은 Matlab을 이용하여 시뮬레이션 한 값과 직접 계산 한 값을 비교하는 방식을 취하였다.

• 한국컴퓨터정보학회논문지
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• 제22권4호
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• pp.9-16
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• 2017

Machine learning has found widespread implementations and applications in many different domains in our life. Logistic regression is a type of classification in machine leaning, and is used widely in many fields, including medicine, economics, marketing and social sciences. In this paper, we present the MapReduce implementation of three existing algorithms, this is, Gradient Descent algorithm, Cost Minimization algorithm and Newton-Raphson algorithm, for logistic regression on RHadoop that integrates R and Hadoop environment applicable to large scale data. We compare the performance of these algorithms for estimation of logistic regression coefficients with real and simulated data sets. We also compare the performance of our RHadoop and RHIPE platforms. The performance experiments showed that our Newton-Raphson algorithm when compared to Gradient Descent and Cost Minimization algorithms appeared to be better to all data tested, also showed that our RHadoop was better than RHIPE in real data, and was opposite in simulated data.

• Journal of Mechanical Science and Technology
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• 제14권6호
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• pp.655-665
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• 2000

We propose an efficient algorithm for the purpose of satisfying a wide range of design constraints represented with equality and inequality equations as well as production rules. The algorithm employs simulated-annealing and a production rule inference engine and works on design constraints represented with networks. The algorithm fulfills equality constraints through constraint satisfaction processes like variable elimination while taking into account inequality constraints and inferring production rules. It can also reduce the load of the optimization procedure if necessary. We demonstrate the implementation of the algorithm with the result on machine tool design.

• 유통과학연구
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• 제10권12호
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• pp.19-24
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• 2012

Purpose - This paper discusses the heterogeneous fixed fleet vehicle routing problem with pick-up and delivery (HFFVRPPD), for vehicles with different capacities, fixed costs, and travel costs. Research Design, data, methodology - This paper made nine assumptions for establishing a mathematical model to describe HFFVRPPD. It established a practical mathematical model, and because of the non-deterministic polynomial-time hard (NP-hard), improved the traditional simulated annealing algorithm and tested a new algorithm using a certain scale model. Result - We calculated the minimum cost of the heterogeneous fixed fleet vehicle routing problem (HFFVRP) with a single task and, on comparing the results with the actual HFFVRP for the single task alone, observed that the total cost of HFFVRPPD reduced significantly by 46.7%. The results showed that the new algorithm provides better solutions and stability. Conclusions - This paper, by comparing the HFFVRP and HFFVRPPD results, highlights certain advantages of using HFFVRPPD in physical distribution enterprises, such as saving distribution vehicles, reducing logistics cost, and raising economic benefits.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2000년도 춘계학술대회논문집A
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• pp.797-802
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• 2000

Flow shop scheduling problem involves processing several jobs on common facilities where a setup time Is incurred whenever there is a switch of jobs. Practical aspect of scheduling focuses on finding a near-optimum solution within a feasible time rather than striving for a global optimum. In this paper, a hybrid meta-heuristic method called tabu-genetic algorithm(TGA) is suggested, which combines the genetic algorithm(GA) with tabu list. The experiment shows that the proposed TGA can reach the optimum solution with higher probability than GA or SA(Simulated Annealing) in less time than TS(Tabu Search). It also shows that consideration of setup time becomes more important as the ratio of setup time to processing time increases.

• 지식경영연구
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• 제10권4호
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• pp.17-30
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• 2009

This study is concerned with suggesting a new clustering algorithm to evaluate the value of papers which were supported by research grants by Korea Research Fund (KRF). The algorithm is based on an extended version of a conventional PSO (Particle Swarm Optimization) mechanism. In other words, the proposed algorithm is based on integration of k-means algorithm and simulated annealing mechanism, named KASA-PSO. To evaluate the robustness of KASA-PSO, its clustering results are evaluated by research grants experts working at KRF. Empirical results revealed that the proposed KASA-PSO clustering method shows improved results than conventional clustering method.

• Journal of Power Electronics
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• 제9권2호
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• pp.198-206
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• 2009

An algorithm is developed that enables a single-phase matrix converter (SPMC) to perform functions of a generalized single phase power electronics converter such as acting as a frequency changer, rectifier, inverter, and chopper. This reduces the need for new converter hardware. The algorithm is implemented first on computer simulation software Orcad Capture CIS version 9.1. Simulation results are presented for five types of converters with a control input variable that decides the 1) type of converter and 2) type of output waveform. The simulated results verify the working and operation of a generalized converter based on SPMC. Simulated results are verified with experimental results. Hardware design is obtained using readily available ICs and other components. The trigger circuit has been tested qualitatively by observing waveforms on CRO. The operation of the proposed system has been found to be satisfactory.

• 융합신호처리학회 학술대회논문집
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• 한국신호처리시스템학회 2001년도 하계 학술대회 논문집(KISPS SUMMER CONFERENCE 2001
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• pp.69-72
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• 2001

High-level synthesis는 주어진 동작과 면적, 성능, 전력 소모, 패키징, 테스팅 등의 주어진 제한을 만족하게 구현된 구조적 디자인을 생성한다. 즉 high-level syntehesis란 디지털 시스템의 알고리즘 레벨 서술로부터 레지스터 전달구조의 구현에 이르는 과정을 의미한다. 이러한 high-level synthesis의 과정은 컴파일, 분할, 스케줄링 등의 단계를 거쳐 디지털 시스템을 설계할 수 있다. 본 논문에서는 high-level synthesis의 단계중 분할 과정을 연구하고, 분할 알고리즘 중에서 min-cut 알고리즘과 simulated annealing 알고리즘을 사용하여 비교 분석하였다.