• Smart Structures and Systems
• /
• v.20 no.1
• /
• pp.99-114
• /
• 2017

In cognitive science, it is illustrated how the collective opinions of a group of individuals answers to questions involving quantity estimation. One example of this approach is introduced in this article as Star Graph (SG) algorithm. This graph describes the details of communication among individuals to share their information and make a new decision. A new labyrinthine network of neighbors is defined in the decision-making process of the algorithm. In order to prevent getting trapped in local optima, the neighboring networks are regenerated in each iteration of the algorithm. In this algorithm, the normal distribution is utilized for a group of agents with the best results (guidance group) to replace the existing infeasible solutions. Here, some new functions are introduced to provide a high convergence for the method. These functions not only increase the local and global search capabilities but also require less computational effort. Various benchmark functions and engineering problems are examined and the results are compared with those of some other algorithms to show the capability and performance of the presented method.

• Proceedings of the KIEE Conference
• /
• 2004.11c
• /
• pp.420-422
• /
• 2004

The non-ideal characteristics of wireless communication are found in sensor network. And sensor network must also address new raised issues. The efficient ad-hoc routing algorithm is considered the nice solution for new raised sensor network problems. To design this efficient ad-hoc routing algorithm, we study and evaluate new components in routing algorithm. Namely, new components are Link estimator, Neighbor table and Parent selection. We have tested this related experiment using the TIP-30C. TIP-30C is sensor network node that is designed by KETI(Korea Electronic Technology Institute).

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2000.11a
• /
• pp.103-106
• /
• 2000

In this paper, we introduce a new evolutionary multiobjective optimization algorithm based on the non-domination direction information, which can be an alternative among several multiobjective evolutionary algorithms. The new evolutionary multiobjective optimization algorithm proposed in this paper will not use the conventional recombination or mutation operators but use the non-domination directions, which are extracted from the non-domination relation among the population. And the problems of the modified sharing algorithms are pointed out and a new sharing algorithm sill be proposed to overcome those problems.

• Proceedings of the Korean Nuclear Society Conference
• /
• 1997.05a
• /
• pp.27-32
• /
• 1997

In this paper, a new multigrid method is developed to solve the reactor eigenvalue problems. The new algorithm can be used in any matrix equation concerned with the eigenvalue problem. The finite difference neutron diffusion problem is considered demonstration of the performance of the new multigrid algorithm. The numerical results show that the new multigrid algorithm works well and requires much shorter (7~10 times) computing time compaired to the production code VENTURE.

• Bulletin of the Korean Mathematical Society
• /
• v.50 no.3
• /
• pp.823-832
• /
• 2013

We present a new algorithm for solving a system of nonlinear equations with convex constraints which combines proximal point and projection methodologies. Compared with the existing projection methods for solving the problem, we use a different system of linear equations to obtain the proximal point; and moreover, at the step of getting next iterate, our projection way and projection region are also different. Based on the Armijo-type line search procedure, a new hyperplane is introduced. Using the separate property of hyperplane, the new algorithm is proved to be globally convergent under much weaker assumptions than monotone or more generally pseudomonotone. We study the convergence rate of the iterative sequence under very mild error bound conditions.

• Transactions of the Korean Society of Mechanical Engineers
• /
• v.18 no.6
• /
• pp.1455-1464
• /
• 1994

A new and efficient algorithm for the integration of the thermal-elasto-plastic constitutive equation is proposed. While it falls into the category of the return mapping method, the algorithm adopts the three point approximation of plastic corrector within one time increment step. The results of its application to a von Mises-type thermal-elasto-plastic model with combined hardening and temperature-dependent material properties show that the accurate iso-error maps are obtained for both angular and radial errors. The accuracy achieved is because the predicted stress increment in a single step calculation follows the exact value closely not only at the end of the step but also through the whole path. Also, the comparison of the computational time for the new and other algorithms shows that the new one is very efficient.

• The Transactions of the Korean Institute of Electrical Engineers P
• /
• v.67 no.3
• /
• pp.131-136
• /
• 2018

Harmony search (HS) is a relatively recently developed meta-heuristic optimization method imitating the music improvisation process where musicians improvise their instruments' pitches searching for a perfect state of harmony. In the conventional HS algorithm, it is necessary to determine the maximum number of iterations with some algorithm parameters. However, there is no criterion for determining the number of iterations, which is a very difficult problem. To solve this problem, a new method is proposed to perform the algorithm without setting the maximum number of iterations in this paper. The new method allows the algorithm to be performed until the desired tuning is achieved. To do this, a new variable bandwidth is introduced. In addition, the types and probability of harmonies composed of variables is analyzed to help to decide the value of HMCR. The performance of the proposed method is investigated and compared with classical HS. The experiments conducted show that the new method generally outperformed conventional HS when applied to seven benchmark problems.

• Journal of applied mathematics & informatics
• /
• v.35 no.1_2
• /
• pp.191-204
• /
• 2017

A new fifth-order weighted Runge-Kutta algorithm based on heronian mean for solving initial value problem in ordinary differential equations is considered in this paper. Comparisons in terms of numerical accuracy and size of the stability region between new proposed Runge-Kutta(5,5) algorithm, Runge-Kutta (5,5) based on Harmonic Mean, Runge-Kutta(5,5) based on Contra Harmonic Mean and Runge-Kutta(5,5) based on Geometric Mean are carried out as well. The problems, methods and comparison criteria are specified very carefully. Numerical experiments show that the new algorithm performs better than other three methods in solving variety of initial value problems. The error analysis is discussed and stability polynomials and regions have also been presented.

• Structural Engineering and Mechanics
• /
• v.34 no.5
• /
• pp.625-634
• /
• 2010

The objective of this paper is to apply a new proposed accuracy indicator to quantify the true and false modes for Eigensystem Realization Algorithm using output-based responses. First, a discrete mass-spring system and a simply supported continuous beam were modelled using finite element method. Then responses are simulated under random excitation. Natural Excitation Technique using only response measurements is applied to compute the impulse responses. Eigensystem Realization Algorithm is employed to identify the modal parameters on the simulated responses. A new accuracy indicator, Normalized Occurrence Number-NON, is developed to quantitatively partition the realized modes into true and false modes so that the false portions can be disregarded. Numerical simulation demonstrates that the new accuracy indicator can determine the true system modes accurately.

• Journal of Korea Society of Industrial Information Systems
• /
• v.4 no.3
• /
• pp.79-88
• /
• 1999

One of the most popular algorithm in adaptive signal processing is the least mean square(LMS) algorithm. The majority of these papers examine the LMS algorithm with a constant step size. The choice of the step size reflects a tradeoff between misadjustment and the speed of adaptation. Subsequent works have discussed the issue of optimization of the step size or methods of varying the step size to improve performance. However there is as yet no detailed analysis of a variable step size algorithm that is capable of giving both the speed of adaptation and convergence. In this paper we propose a new variable step size algorithm where the step size adjustment is controlled by square of the prediction error. The simulation results obtained using the new algorithm about noise canceller system and system identification are described. They are compared to the results obtained for other variable step size algorithm. function.