• 제목/요약/키워드: New Algorithm

검색결과 11,736건 처리시간 0.036초

A New Green Clustering Algorithm for Energy Efficiency in High-Density WLANs

  • Lu, Yang;Tan, Xuezhi;Mo, Yun;Ma, Lin
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제8권2호
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    • pp.326-354
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    • 2014
  • In this paper, a new green clustering algorithm is proposed to be as a first approach in the framework of an energy efficient strategy for centralized enterprise high-density WLANs. Traditionally, in order to maintain the network coverage, all the APs within the WLAN have to be powered-on. Nevertheless, the new algorithm can power-off a large proportion of APs while the coverage is maintained as its always-on counterpart. The two main components of the new approach are the faster procedure based on K-means and the more accurate procedure based on Evolutionary Algorithm (EA), respectively. The two procedures are processes in parallel for different designed requirements and there is information interaction in between. In order to implement the new algorithm, EA is applied to handle the optimization of multiple objectives. Moreover, we adapt the method for selection and recombination, and then introduce a new operator for mutation. This paper also presents simulations in scenarios modeled with ray-tracing method and FDTD technique, and the results show that about 67% to 90% of energy consumption can be saved while it is able to maintain the original network coverage during periods when few users are online or the traffic load is low.

Fast Sub-aperture Stitching Algorithm Using Partial Derivatives

  • Chen, Yiwei;Miao, Erlong;Sui, Yongxin;Yang, Huaijiang
    • Journal of the Optical Society of Korea
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    • 제19권1호
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    • pp.84-87
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    • 2015
  • For large optical elements which are tested by many sub-apertures, it takes too much time for a sub-aperture stitching algorithm to get the stitching result. To solve this problem, we propose a fast sub-aperture stitching algorithm to quickly compensate for piston, tilt, and defocus errors. Moreover, the new algorithm is easy to understand and program. We use partial derivatives of measurement data to separately solve piston, tilt, and defocus errors. First, we show that the new algorithm has a lower time complexity than the currently used algorithm. Although simulation results indicate that the accuracy of the new algorithm is lower than the current algorithm in all 20 simulations, our experimental results validate the algorithm and show it is sufficiently accurate for general use.

비대칭 손상 선박의 잔류 종강도 평가를 위한 간이 해석 알고리즘 개발 (Development of a New Simplified Algorithm for Residual Longitudinal Strength Prediction of Asymmetrically Damaged Ships)

  • 정준모;남지명;이민성;전상익;하태범
    • 대한조선학회논문집
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    • 제48권3호
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    • pp.281-287
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    • 2011
  • This paper explains the basic theory and a new development of for the residual strength prediction program of the asymmetrically damaged ships, being capable of searching moment-curvature relations considering neutral axis mobility. It is noted that moment plane and neutral axis plane should be separately defined for asymmetric sections. The validity of the new program is verified by comparing moment-curvature curves of 1/3 scaled frigate model where the results from new algorithm well coincide with experimental and nonlinear FEA results for intact condition and with nonlinear FEA results for damaged condition. Applicability of new algorithm is also verified by applying VLCC model to the newly developed program. It is proved that reduction of residual strengths is visually presented using the new algorithm when damage specifications of ABS, DNV and IMO are applied. It is concluded that the new algorithm shows very good performance to produce moment-curvature relations with neutral axis mobility on the asymmetrically damaged ships. It is expected that the new program based on the developed algorithm can largely reduce design period of FE modeling and increase user conveniences.

A new hybrid meta-heuristic for structural design: ranked particles optimization

  • Kaveh, A.;Nasrollahi, A.
    • Structural Engineering and Mechanics
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    • 제52권2호
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    • pp.405-426
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    • 2014
  • In this paper, a new meta-heuristic algorithm named Ranked Particles Optimization (RPO), is presented. This algorithm is not inspired from natural or physical phenomena. However, it is based on numerous researches in the field of meta-heuristic optimization algorithms. In this algorithm, like other meta-heuristic algorithms, optimization process starts with by producing a population of random solutions, Particles, located in the feasible search space. In the next step, cost functions corresponding to all random particles are evaluated and some of those having minimum cost functions are stored. These particles are ranked and their weighted average is calculated and named Ranked Center. New solutions are produced by moving each particle along its previous motion, the ranked center, and the best particle found thus far. The robustness of this algorithm is verified by solving some mathematical and structural optimization problems. Simplicity of implementation and reaching to desired solution are two main characteristics of this algorithm.

Bezier Spline을 이용한 용접 로봇의 새로운 Weaving Motion 궤적 생성 알고리즘 (A New Planning Algorithm of Weaving Trajectory Using Bezier Spline for A Welding Robot)

  • 정원지;김대영;서영교;홍형표;홍대선
    • 한국공작기계학회논문집
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    • 제13권3호
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    • pp.113-118
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    • 2004
  • In this paper, we propose a new weaving trajectory algorithm for the arc welding of a articulated manipulator. The algorithm uses the theory of Bezier spline. We make a comparison between the conventional algorithms using Catmull-Rom curve and the new algorithms using Bezier spline. The proposed algorithm has been evaluated based on the MATLAB environment in order to illustrate its good performance. Through simulations, the proposed algorithm can result in high-speed and flexible weaving trajectory planning so that it's trajectory cannot penetrate into a base metal compared to the conventional algorithm using Catmull-Rom curve.

멀티모달 함수의 최적화를 위한 먼델 연산 유전자 알고리즘 (A Genetic Algorithm with a Mendel Operator for Multimodal Function Optimization)

  • 송인수;심재완;탁민제
    • 제어로봇시스템학회논문지
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    • 제6권12호
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    • pp.1061-1069
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    • 2000
  • In this paper, a new genetic algorithm is proposed for solving multimodal function optimization problems that are not easily solved by conventional genetic algorithm(GA)s. This algorithm finds one of local optima first and another optima at the next iteration. By repeating this process, we can locate all the local solutions instead of one local solution as in conventional GAs. To avoid converging to the same optimum again, we devise a new genetic operator, called a Mendel operator which simulates the Mendels genetic law. The proposed algorithm remembers the optima obtained so far, compels individuals to move away from them, and finds a new optimum.

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완전 이식형 인공심장의 심박출량 자동 제어 알고리즘 개발에 관한 연구 (Development of an Automatic Cardiac Output Control Algorithm for the Total Artificial Heart)

  • 최원우;김희찬;민병구
    • 전자공학회논문지B
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    • 제32B권3호
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    • pp.38-47
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    • 1995
  • A new automatic cardiac output control algorithm for the motor-driven electromechanical total artificial heart(TAH) was developed based on the motor current waveform analysis without using any extra transducer. The basic control requirements of artificial heart can be described in terms of three features : preload sensitivity, afterload insensitivity, and balanced ventricular outputs. In the previous studies, many transducers were utilized to obtain informations of hemodynamic states for the automatic cardiac output control, But such automatic control systems with sensors have had reliability problems. We proposed a new sensorless automatic cardiac output control algorithm providing adequate cardiac output to the time-varying physiological demand without causing right atrial collapse, which is one of the critical problem in an active-filling type device. In-vitro tests were performed on a mock circulation system to evaluate the performance of the developed algorithm and the results show that the new algorithm satisfied the basic control requirements on the cardiac output response and the possibility of application of the developed algorithm to in vivo experiments.

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유전알고리즘에서 선형제약식을 다루는 방법 (A Handling Method of Linear Constraints for the Genetic Algorithm)

  • 성기석
    • 한국경영과학회지
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    • 제37권4호
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    • pp.67-72
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    • 2012
  • In this paper a new method of handling linear constraints for the genetic algorithm is suggested. The method is designed to maintain the feasibility of offsprings during the evolution process of the genetic algorithm. In the genetic algorithm, the chromosomes are coded as the vectors in the real vector space constrained by the linear constraints. A method of handling the linear constraints already exists in which all the constraints of equalities are eliminated so that only the constraints of inequalities are considered in the process of the genetic algorithm. In this paper a new method is presented in which all the constraints of inequalities are eliminated so that only the constraints of equalities are considered. Several genetic operators such as arithmetic crossover, simplex crossover, simple crossover and random vector mutation are designed so that the resulting offspring vectors maintain the feasibility subject to the linear constraints in the framework of the new handling method.

적응 군집화 기법과 유전 알고리즘을 이용한 영상 영역화 (Image segmentation using adaptive clustering algorithm and genetic algorithm)

  • 하성욱;강대성
    • 전자공학회논문지S
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    • 제34S권8호
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    • pp.92-103
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    • 1997
  • This paper proposes a new gray-level image segmentation method using GA(genetic algorithm) and an ACA(adaptive clustering algorithm). The solution in the general GA can be moving because of stochastic reinsertion, and suffer from the premature convergence problem owing to deficiency of individuals before finding the optimal solution. To cope with these problems and to reduce processing time, we propose the new GBR algorithm and the technique that resolves the premature convergence problem. GBR selects the individual in the child pool that has the fitness value superior to that of the individual in the parents pool. We resolvethe premature convergence problem with producing the mutation in the parents population, and propose the new method that removes the small regions in the segmented results. The experimental results show that the proposed segmentation algorithm gives better perfodrmance than the ACA ones in Gaussian noise environments.

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A new PSRO algorithm for frequency constraint truss shape and size optimization

  • Kaveh, A.;Zolghadr, A.
    • Structural Engineering and Mechanics
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    • 제52권3호
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    • pp.445-468
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    • 2014
  • In this paper a new particle swarm ray optimization algorithm is proposed for truss shape and size optimization with natural frequency constraints. These problems are believed to represent nonlinear and non-convex search spaces with several local optima and therefore are suitable for examining the capabilities of new algorithms. The proposed algorithm can be viewed as a hybridization of Particle Swarm Optimization (PSO) and the recently proposed Ray Optimization (RO) algorithms. In fact the exploration capabilities of the PSO are tried to be promoted using some concepts of the RO. Five numerical examples are examined in order to inspect the viability of the proposed algorithm. The results are compared with those of the PSO and some other existing algorithms. It is shown that the proposed algorithm obtains lighter structures in comparison to other methods most of the time. As will be discussed, the algorithm's performance can be attributed to its appropriate exploration/exploitation balance.