• Proceedings of the KIEE Conference
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• 1998.11a
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• pp.259-262
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• 1998

This paper presents a new eigenvalue calculation methods in AESOPS algorithm. The source program of the AESOPS algorithm is modified to practice in PC environment. Window95 is used as an operating system of PC and MicroSoft Power Station is used to compile the fortran source program. The heuristically approximated eigenvalue calculation method of the AESOPS algorithm is transformed to the Newton Raphson Method which is largely used in the nonlinear numerical analysis. The new methods are developed from the AESOPS algorithm and thus only a few calculation steps are added to practice the proposed algorithm.

• Journal of the Korean Data and Information Science Society
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• v.27 no.4
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• pp.911-923
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• 2016

Machine learning becomes increasingly important in the big data era. Logistic regression is a type of classification in machine leaning, and has been widely used in various fields, including medicine, economics, marketing, and social sciences. Rhipe that integrates R and Hadoop environment, has not been discussed by many researchers owing to the difficulty of its installation and MapReduce implementation. In this paper, we present the MapReduce implementation of Gradient Descent algorithm and Newton-Raphson algorithm for logistic regression using Rhipe. The Newton-Raphson algorithm does not require a learning rate, while Gradient Descent algorithm needs to manually pick a learning rate. We choose the learning rate by performing the mixed procedure of grid search and binary search for processing big data efficiently. In the performance study, our Newton-Raphson algorithm outpeforms Gradient Descent algorithm in all the tested data.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1624-1627
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• 1997

The 6-DOF parallel manipulator is a closed-kindmatic chain robot manipulator that is capable of providing high structural rigidity and positional accuracy. Because of its advantage, the parallel manipulator have been widely used in many engineering applications such as vehicle/flight driving simulators, rogot maniplators, attachment tool of machining centers, etc. However, the kinematic analysis for the implementation of a real-time controller has some problem because of the lack of an efficient lagorithm for solving its highly nonliner forward kinematic equation, which provides the translational and orientational attitudes of the moveable upper platform from the lenght of manipulator linkages. Generally, Newton-Raphson method has been widely sued to solve the forward kinematic problem but the effectiveness of this methodology depend on how to set initial values. This paper proposes a hybrid method using genetic algorithm(GA) and Newton-Raphson method to solve forward kinematics. That is, the initial values of forward kinematics solution are determined by adopting genetic algorithm which can search grobally optimal solutions. Since determining this values, the determined values are used in Newton-Raphson method for real time calcuation.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.25 no.3
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• pp.339-352
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• 2001

The inverse kinematics problem of Stewart platform is straightforward, but no closed form solution of the forward kinematic problem has been presented. Since we need the real-time forward kinematic solution in MIMO control and the motion monitoring of the platform, it is important to acquire the 6 DOF displacements of the platform from measured lengths of six cylinders in small sampling period. Newton-Raphson method a simple algorithm and good convergence, but it takes too long calculation time. So we reduce 6 nonlinear kinematic equations to 3 polynomials using Nairs method and 3 polynomials to 2 polynomials. Then Newton-Raphson method is used to solve 3 polynomials and 2 polynomials respectively. We investigate operation counts and performance of three methods which come from the equation reduction and Newton-Raphson method, and choose the best method.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2968-2970
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• 2000

시계열(time series)이란 한 사상 또는 여러 사상에 대하여 시간의 흐름에 따라 일정한 간격으로 이들을 관측하여 기록한 자료를 말한다. 이러한 시계열은 어떠한 경제현상이나 자연현상에 관한 시간적 변화를 나타내는 역사적 계열(historical series)이므로 어느 한 시점에서 관측된 시계열자료는 그 이전까지의 자료들에 주로 의존하게 된다. 따라서 시계열분석을 통한 예측에서는 과거의 자료들을 분석하여 법칙성을 발견해서 이를 모형화하여 추정하고. 이 추정된 모형을 사용하여 미래에 관측될 값들을 예측하게 된다. 본 연구에서는 ARMA (p, q)모형 (autoregressive moving-average model)을 이용하여 시계열 데이터를 분석하며 계수의 추정에는 Levinson-Durbin 알고리듬과 Newton-Raphson Method를 이용한다.

• Proceedings of the KIEE Conference
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• 2000.07a
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• pp.274-275
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• 2000

This paper introduces new ordering algorithms using the graph of data structure and forward/backward substitution of LU decomposition using recursive function. The performance of the algorithm is compared with Tinney's algorithm using 14 bus systems. Test results show that the new fill-in element of Jacobian matrix using the proposed ordering algorithm is same as that of Tinner scheme 3 and the forward/backward substitution can reduce the computation time

• Proceedings of the KIEE Conference
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• 2003.11c
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• pp.875-877
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• 2003

This paper use fault location algorithm for single-phase-to-ground faults on the teed circuit of a parallel transmission line that use only local end voltage and current information. When Newton-Raphson iteration method is used, the Initial value may cause error or cause not suitable result. Suggested new calculation model uses NVP methodology, which is one of the fault tolerance technology to solve this problem. EMTP simulation result has shown effectiveness of the algorithm under various conditions.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.9
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• pp.1081-1087
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• 1999

Load Flow calulation methods can usually be divided into Gauss-Seidel method, Newton-Raphson method and decoupled method. Load flow calculation is a basic on-line or off-line process for power system planning. operation, control and state analysis. These days Newton-Raphson method is mainly used since it shows remarkable convergence characteristics. It, however, needs considerable calculation time in construction and calculation of inverse Jacobian matrix. In addition to that, Newton-Raphson method tends to fail to converge when system loading is heavy and system has a large R/X ratio. In this paper, matrix equation is used to make algebraic expression and then to slove load flow equation and to modify above defects. And it preserve P-Q bus part of Jacobian matrix to shorten computing time. Application of mentioned algorithm to 14 bus, 39 bus, 118 bus systems led to identical results and the same numbers of iteration obtained by Newton-Raphson method. The effect of computing time reduction showed about 28% , 30% , at each case of 39 bus, 118 bus system.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.21 no.4
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• pp.375-382
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• 2008

The particular integral formulation for two(2D) and three(3D) dimensional inelastic transient dynamic stress analysis is presented. The elastostatic equation is used for the complementary solution. Using the concept of global shape function, the particular integrals for displacement and traction rates are obtained to approximate acceleration of the inhomogeneous equation. The Houbolt time integration scheme is used for the time-marching process. The Newton-Raphson algorithm for plastic multiplier is used to solve the system equation. Numerical results of four example problems are given to demonstrate the validity and accuracy of the present formulation.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.1
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• pp.46-55
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• 2007

The Newton-Raphson's algorithm for finding a floating point reciprocal and inverse square root calculates the result by performing a fixed number of multiplications. In this paper, an improved Newton-Raphson's algorithm is proposed, that performs multiplications a variable number. Since the number of multiplications performed by the proposed algorithm is dependent on the input values, the average number of multiplications per an operation is derived from many reciprocal and inverse square tables with varying sizes. The superiority of this algorithm is proved by comparing this average number with the fixed number of multiplications of the conventional algorithm. Since the proposed algorithm only performs the multiplications until the error gets smaller than a given value, it can be used to improve the performance of a reciprocal and inverse square root unit. Also, it can be used to construct optimized approximate tables. The results of this paper can be applied to many areas that utilize floating point numbers, such as digital signal processing, computer graphics, multimedia, scientific computing, etc.