• Title/Summary/Keyword: solve the problem

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The Efficiency of Boosting on SVM

  • Seok, Kyung-Ha;Ryu, Tae-Wook
    • Journal of the Korean Data and Information Science Society
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    • v.13 no.2
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    • pp.55-64
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    • 2002
  • In this paper, we introduce SVM(support vector machine) developed to solve the problem of generalization of neural networks. We also introduce boosting algorithm which is a general method to improve accuracy of some given learning algorithm. We propose a new algorithm combining SVM and boosting to solve classification problem. Through the experiment with real and simulated data sets, we can obtain better performance of the proposed algorithm.

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An Analog Multi-phase DLL for Harmonic Lock Free (Harmonic Locking을 제거하기 위한 아날로그 Multi- phase DLL 설계)

  • 문장원;곽계달
    • Proceedings of the IEEK Conference
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    • 2001.06b
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    • pp.281-284
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    • 2001
  • This paper describes an analog multi-phase delay-locked loop (DLL) to solve the harmonic lock problem using current-starved inverter and shunt-capacitor delay cell. The DLL can be used not only as an internal clock buffer of microprocessors and memory It's but also as a multi-phase clock generator for gigabit serial interfaces. The proposed circuit was simulated in a 0.25${\mu}{\textrm}{m}$ CMOS technology to solve harmonic lock problem and to realize fast lock-on time and low-jitter we verified time interval less than 40 ps as the simulation results.

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Expert System for Project Selection using Goal Programming (목적계획법을 이용한 프로젝트의 선택을 위한 전문가 시스템 개발)

  • 강경규;김창은;이상호
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.19 no.38
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    • pp.131-138
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    • 1996
  • In real world, the organization has multiple objects. Inorder to solve the multiple objects, we present the goal programming for solving project selection problem we also developed expert system which is focused on function of analysis. User which doesn't have knowledge of goal programming can solve the project selection problem and get a result of analysis.

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FMS scheduling through artificial neural network (인공 뉴럴 네트워크에 의한 FMS 일정관리)

  • 양정문;문기주;김정자
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.18 no.34
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    • pp.99-106
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    • 1995
  • Recently, neural network is recognized as a new approach to solve jobshop scheduling problems in manufacturing system. Scheduling problem is known to be a difficult combinational explosive problem with domain-dependence variations in general. In addition, the needs to achieve a good performance in flexible manufacturing system increase the dimensions of decision complexity. Therefore, mathematical approach to solve realistic problems could be failed to find optimal or optimal-trending. In this paper a technique with neural network for jobs grouping by job-attributes and Gaussian machine network for generating to near-optimal sequence is presented.

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A Parallel Algorithm for Large DOF Structural Analysis Problems (대규모 자유도 문제의 구조해석을 위한 병렬 알고리즘)

  • Kim, Min-Seok;Lee, Jee-Ho
    • Journal of the Computational Structural Engineering Institute of Korea
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    • v.23 no.5
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    • pp.475-482
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    • 2010
  • In this paper, an efficient two-level parallel domain decomposition algorithm is suggested to solve large-DOF structural problems. Each subdomain is composed of the coarse problem and local problem. In the coarse problem, displacements at coarse nodes are computed by the iterative method that does not need to assemble a stiffness matrix for the whole coarse problem. Then displacements at local nodes are computed by Multi-Frontal Sparse Solver. A parallel version of PCG(Preconditioned Conjugate Gradient Method) is developed to solve the coarse problem iteratively, which minimizes the data communication amount between processors to increase the possible problem DOF size while maintaining the computational efficiency. The test results show that the suggested algorithm provides scalability on computing performance and an efficient approach to solve large-DOF structural problems.

Multi-target Classification Method Based on Adaboost and Radial Basis Function (아이다부스트(Adaboost)와 원형기반함수를 이용한 다중표적 분류 기법)

  • Kim, Jae-Hyup;Jang, Kyung-Hyun;Lee, Jun-Haeng;Moon, Young-Shik
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.47 no.3
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    • pp.22-28
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    • 2010
  • Adaboost is well known for a representative learner as one of the kernel methods. Adaboost which is based on the statistical learning theory shows good generalization performance and has been applied to various pattern recognition problems. However, Adaboost is basically to deal with a two-class classification problem, so we cannot solve directly a multi-class problem with Adaboost. One-Vs-All and Pair-Wise have been applied to solve the multi-class classification problem, which is one of the multi-class problems. The two methods above are ones of the output coding methods, a general approach for solving multi-class problem with multiple binary classifiers, which decomposes a complex multi-class problem into a set of binary problems and then reconstructs the outputs of binary classifiers for each binary problem. However, two methods cannot show good performance. In this paper, we propose the method to solve a multi-target classification problem by using radial basis function of Adaboost weak classifier.

Digital Image Enhancement Algorithm

  • Yoo, Suk Won
    • International Journal of Advanced Culture Technology
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    • v.4 no.3
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    • pp.48-55
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    • 2016
  • Conventional techniques for solving the noise problem have problems to generate different results, depending on the image size and weight values of the used masks, and they require many operations by using a complex formula. In this paper, we propose an image enhancement algorithm to solve the noise problem in a simple, yet easy-to-use way. For this purpose, we determined the difference between the noise of the two adjacent pixels for the horizontal and vertical, and for the two diagonal directions that each of the noise problem occurred, and then we got the average value of these pixel values. Then, we solve the noise problem by using the optimal average value in accordance with occurrence of the noise in the horizontal and vertical, and two adjacent pixels in a diagonal direction. As a result, we got the result that the noise solution in a simple, yet easy-to-use method to obtain a resultant image.

SOLVING A SYSTEM OF THE NONLINEAR EQUATIONS BY ITERATIVE DYNAMIC PROGRAMMING

  • Effati, S.;Roohparvar, H.
    • Journal of applied mathematics & informatics
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    • v.24 no.1_2
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    • pp.399-409
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    • 2007
  • In this paper we use iterative dynamic programming in the discrete case to solve a wide range of the nonlinear equations systems. First, by defining an error function, we transform the problem to an optimal control problem in discrete case. In using iterative dynamic programming to solve optimal control problems up to now, we have broken up the problem into a number of stages and assumed that the performance index could always be expressed explicitly in terms of the state variables at the last stage. This provided a scheme where we could proceed backwards in a systematic way, carrying out optimization at each stage. Suppose that the performance index can not be expressed in terms of the variables at the last stage only. In other words, suppose the performance index is also a function of controls and variables at the other stages. Then we have a nonseparable optimal control problem. Furthermore, we obtain the path from the initial point up to the approximate solution.

Improved Resource Allocation Scheme in LTE Femtocell Systems based on Fractional Frequency Reuse

  • Lee, Insun;Hwang, Jaeho;Jang, Sungjeen;Kim, Jaemoung
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.6 no.9
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    • pp.2153-2169
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    • 2012
  • Femtocells provide high quality indoor communications with low transmit power. However, when femtocells are applied in cellular systems, a co-channel interference problem between macrocells and femtocells occurs because femtocells use the same spectrum as do the macrocells. To solve the co-channel interference problem, a previous study suggested a resource allocation scheme in LTE cellular systems using FFR. However, this conventional resource allocation scheme still has interference problems between macrocells and femtocells near the boundary of the sub-areas. In this paper, we define an optimization problem for resource allocation to femtocells and propose a femtocell resource allocation scheme to solve the optimization problem and the interference problems of the conventional scheme. The evaluation of the proposed scheme is conducted by System Level Simulation while varying the simulation environments. The simulation results show that the proposed scheme is superior to the conventional scheme and that it improves the overall performance of cellular systems.

Energy Aware Routing Protocol over Wireless Sensor Network (센서 네트워크에서 에너지 보유량을 고려한 라우팅 프로토콜)

  • Choi, Hae-Won;Yoo, Kee-Young
    • Journal of Korea Society of Industrial Information Systems
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    • v.13 no.2
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    • pp.28-34
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    • 2008
  • This paper reports the problem in the previous routing protocol, EAR, and proposes an energy aware routing protocol to solve the problem in it. Proposed routing protocol considers the number of hops, the possibility of node exhaustion, and the node energy amount at the same time from the source to the sink. Thereby, it could efficiently solve the potential network separation problem and the sensing hole problem in EAR. Proposed routing protocol could remove the problems in the previous routing protocols but it still gets the advantages in them.

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