• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.10
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• pp.3789-3809
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• 2015

In this paper, we deal with the problem of M2M gateways' network selection for different types of M2M traffic in heterogeneous wireless networks. Based on the difference in traffic's quality of service (QoS) requirements, the M2M traffic produced by various applications is mainly classified as two categories: flexible traffic and rigid traffic. Then, game theory is adopted to solve the problem of network-channel selection with the coexistence of flexible and rigid traffic, named as flexible network access (FNA). We prove the formulated discrete game is a potential game. The existence and feasibility of the Nash equilibrium (NE) of the proposed game are also analyzed. Then, an iterative algorithm based on optimal reaction criterion and a distributed algorithm with limited feedback based on learning automata are presented to obtain the NE of the proposed game. In simulations, the proposed iterative algorithm can achieve a near optimal sum utility of whole network with low complexity compared to the exhaustive search. In addition, the simulation results show that our proposed algorithms outperform existing methods in terms of sum utility and load balance.

• Bulletin of the Korean Mathematical Society
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• v.60 no.5
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• pp.1181-1199
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• 2023

For solving complex symmetric positive definite linear systems, we propose a single step real-valued (SSR) iterative method, which does not involve the complex arithmetic. The upper bound on the spectral radius of the iteration matrix of the SSR method is given and its convergence properties are analyzed. In addition, the quasi-optimal parameter which minimizes the upper bound for the spectral radius of the proposed method is computed. Finally, numerical experiments are given to demonstrate the effectiveness and robustness of the propose methods.

• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.2092-2095
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• 2001

In this paper, the performance of a new alternative form of three-axis attitude estimation algorithm for a rigid body is evaluated via simulation for the situation where the observed vectors are the estimated baselines of a GPS antenna array. This method is derived based on a simple iterative nonlinear least-squares with four elements of quaternion parameter. The representation of quaternion parameters for three-axis attitude of a rigid body is free from singularity problem. The performance of the proposed algorithm is compared with other eight existing methods, such as, Transformation Method (TM), Vector Observation Method (VOM), TRIAD algorithm, two versions of QUaternion ESTimator (QUEST), Singular Value Decomposition (SVD) method, Fast Optimal Attitude Matrix (FOAM), Slower Optimal Matrix Algorithm (SOMA).

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1994.04a
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• pp.103-111
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• 1994

An interactive and iterative design method based on the constraint satisfaction problem (CSP) technique was developed to generate an ergonomically sound layout of a control panel. This control panel layout method attempts to incorporate a variety of relevant ergonomic principles and design constraints, and generate an optimal or, at least, a "satisfactory" solution through iterative interactions with the designer. The existing panel design and layout methods are mostly based on the optimization of single objective function formulated to reflect and trade off all ergonomic design objectives which are largely different in their nature. In fact, the problem of seeking an ergonomically sound panel design should be viewed as a multiple objective optimization problem. Furthermore, most of the design objectives should be understood as constraints rather than objectives to be optimized. Hence, a constraint satisfaction approach is proposed in this study as a framework for the panel designer to search through the design decision space effectively and make various design decisions iteratively. In order to apply the constraint satisfaction approach to the panel design procedure, the ergonomic principles such as frequency-of-use, importance, functional grouping, and sequence-of-use are formalized as CSP terms. With this formalization, a prototype system was implemented and applied to panel layout problems. The results clearly showed the effectiveness of the proposed approach since it permits designers to consider and iteratively evaluate various design constraints and ergonomic principles, and, therefore, aids the panel designer to come up with an ergonomically sound control panel layout.

• Structural Engineering and Mechanics
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• v.46 no.5
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• pp.735-753
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• 2013

The wind load is always the dominant load of cooling tower due to its large size, complex geometry and thin-wall structure. At present, when computing the wind-induced response of the large-scale cooling tower, the wind pressure distribution is obtained based on code regulations, wind tunnel test or computational fluid dynamic (CFD) analysis, and then is imposed on the tower structure. However, such method fails to consider the change of the wind load with the deformation of cooling tower, which may result in error of the wind load. In this paper, the analysis of the large cooling tower based on the iterative method for wind pressure is studied, in which the advantages of CFD and finite element method (FEM) are combined in order to improve the accuracy. The comparative study of the results obtained from the code regulations and iterative method is conducted. The results show that with the increase of the mean wind speed, the difference between the methods becomes bigger. On the other hand, based on the design of experiment (DOE), an approximate model is built for the optimal design of the large-scale cooling tower by a two-level optimization strategy, which makes use of code-based design method and the proposed iterative method. The results of the numerical example demonstrate the feasibility and efficiency of the proposed method.

• Journal of applied mathematics & informatics
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• v.24 no.1_2
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• pp.245-259
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• 2007

This paper studies some properties of the value functions and gives some sufficient and necessary conditions about the presented global error and local error. And it leads to one kind of relationship between iterative points and optimal solution or K-T point.

• Communications for Statistical Applications and Methods
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• v.6 no.3
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• pp.843-848
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• 1999

Support vector machine(SVM) is a new and very promising classification and regression technique developed by Bapnik and his group at AT&T Bell laboratories. However it has failed to establish itself as common machine learning tool. This is partly due to the fact that SVM is not easy to implement and its standard implementation requires the optimization package for quadratic programming. In this paper we present simple iterative Kernl Adatron algorithm for nonparametric regression which is easy to implement and guaranteed to converge to the optimal solution and compare it with neural networks and projection pursuit regression.

• Journal of applied mathematics & informatics
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• v.30 no.3_4
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• pp.395-411
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• 2012

Several methods with order higher than that of Newton methods which are of order 2 have been reported in literature for solving nonlinear equations. The focus of most of these methods was to economize on/minimize the number of function evaluations per iterations. We have demonstrated here that there are several computational pit-falls, such as the violation of fixed-point theorem, that one could encounter while using these methods. Further it was also shown that the overall computational complexity could be more in these high-order methods than that in the second-order Newton method.

• Korean System Dynamics Review
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• v.13 no.2
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• pp.47-71
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• 2012

The purpose of this research is the examination of validity of data as well as simulation model, i.e. to simulate the real data in the SD model with the least error using the adjustments for the faithful reflection of real data to the simulation. In general, SD programs (e.g. VENSIM) utilize the Euler or Runge-Kutta method as an algorithm. It is possible to reflect the trend of real data via these two estimation methods however can cause the validity problem in case of the simulation requiring the accuracy as they have endogenous errors. In this article, the future population estimated by the Korea National Statistical Office (KNSO) to 2050 is simulated by the aging chain model, dividing the population into three cohorts, 0-14, 15-64, 65 and over cohorts by age and offering the adjustments to them. Adjustments are calculated by optimization with three different methods, optimization in EXCEL, manual optimization with iterative calculation, and optimization in VENSIM DSS, the results are compared, and at last the optimal adjustment set with the least error are found among them. The simulation results with the pre-determined optimal adjustment set are validated by methods proposed by Barlas (1996) and other alternative methods. It is concluded that the result of simulation model in this research has no significant difference from the real data and reflects the real trend faithfully.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.6
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• pp.979-986
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• 2016

At present, electric power industry around the world are being gradually changed to a new paradigm, such as electrical energy storage system, the wireless power transmission. Demand for ESS, the core technology of the new paradigm, has been growing worldwide. However, it is essential to estimate the optimal capacity of ESS facilities for frequency regulation because the benefit would be saturated in accordance with the investment moment and the increase of total invested capacity of ESS facilities. Hence, in this paper, the annual optimal mathematical investment model is proposed to estimate the optimal capacity and to establish investment plan of ESS facility for frequency regulation. The optimal mathematical investment model is newly established for each season, because the construction period is short and the operation effect for the load by seasons is different unlike previous the mathematical investment model. Additionally, the marginal operating cost is found by new mathematical operation model considering no-load cost and start-up cost as step functions improving the previous mathematical operation model. ESS optimal capacity is established by use value in use iterative methods. In this case, ESS facilities cost is used in terms of the value of the beginning of the year.