• Journal of international Conference on Electrical Machines and Systems
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• v.2 no.1
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• pp.16-22
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• 2013

This paper presents the analysis and optimization of air-core permanent magnet linear synchronous motor with overlapping concentrated windings to achieve high thrust density, high thrust per copper losses and low thrust ripple. For the motor design, we adopt equivalent magnetizing current (EMC) method to analyze the magnetic field and give analytical formulae for calculation of motor parameters such as no-load back EMF, dynamic force, thrust density and thrust per copper losses. Further, we proposed a multi-objective optimization by genetic algorithm to search for the optimum parameters. The design optimization is verified by 2-D Finite Element analysis (FEA).

• Journal of Communications and Networks
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• v.17 no.1
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• pp.1-11
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• 2015

In this paper, the transmission of an improper-complex second-order stationary data sequence is considered over a strictly band-limited frequency-selective channel. It is assumed that the transmitter employs linear modulation and that the channel output is corrupted by additive proper-complex cyclostationary noise. Under the average transmit power constraint, the problem of minimizing the mean-squared error at the output of a widely linear receiver is formulated in the time domain to find the optimal transmit and receive waveforms. The optimization problem is converted into a frequency-domain problem by using the vectorized Fourier transform technique and put into the form of a double minimization. First, the widely linear receiver is optimized that requires, unlike the linear receiver design with only one waveform, the design of two receive waveforms. Then, the optimal transmit waveform for the linear modulator is derived by introducing the notion of the impropriety frequency function of a discrete-time random process and by performing a line search combined with an iterative algorithm. The optimal solution shows that both the periodic spectral correlation due to the cyclostationarity and the symmetric spectral correlation about the origin due to the impropriety are well exploited.

• Biomaterials and Biomechanics in Bioengineering
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• v.2 no.4
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• pp.207-223
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• 2015

In this paper a method for simultaneous swift non-linear analysis and optimal design/posture of mechanical/biomechanical systems is presented. The method is developed to get advantages of iterations in non-linear analysis and/or generations in genetic algorithm (GA) for the purpose of efficient analysis within the optimal design/posture. The method is applicable for both size and geometry optimizations wherein material and geometry non-linearity are present. In addition to established mechanical systems, the method can solve biomechanical models of human musculoskeletal system. Optimization-based procedures are popular methods for resolving the redundancy at joints wherein the number of unknown muscle forces is far more than the number of equilibrium equations. These procedures involve optimization of a cost function(s) which is assumed to be consistent with the central nervous system's strategy when activating muscles to assure equilibrium. However, because of the complexity of biomechanical problems (i.e., due to non-linear biomaterial, large deformation, redundancy of the problem and so on) efficient analysis are required within optimization procedures as suggested in this paper.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.3
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• pp.139-143
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• 2023

The product portfolio problem(PPP) is an optimization problem that determines the production quantity of a particular product to obtain the maximum profit among the n products. Linear programming(LP) is known as the only way to solve this optimization problem. The linear programming method is a problem that optimizes n linear functions and uses LINGO or Excel solver. This paper proposes a simple algorithm that uses CPR, a product cost-profit ratio, to sort in CPR descending order and then determines the maximum allowed production quantity by hand as the actual production quantity. As a result of applying the proposed algorithm to six experimental data, it was shown that more accurate results can be obtained compared to the linear programming method.

• Journal of Electrical Engineering and Technology
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• v.12 no.2
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• pp.911-917
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• 2017

There are generally three folds when developing neural network classifiers. They are as follows: 1) discriminant function; 2) lots of parameters in the design of classifier; and 3) high dimensional training data. Along with this viewpoint, we propose space search optimized polynomial neural network classifier (PNNC) with the aid of data preprocessing technique and simultaneous tuning strategy, which is a balance optimization strategy used in the design of PNNC when running space search optimization. Unlike the conventional probabilistic neural network classifier, the proposed neural network classifier adopts two type of polynomials for developing discriminant functions. The overall optimization of PNNC is realized with the aid of so-called structure optimization and parameter optimization with the use of simultaneous tuning strategy. Space search optimization algorithm is considered as a optimize vehicle to help the implement both structure and parameter optimization in the construction of PNNC. Furthermore, principal component analysis and linear discriminate analysis are selected as the data preprocessing techniques for PNNC. Experimental results show that the proposed neural network classifier obtains better performance in comparison with some other well-known classifiers in terms of accuracy classification rate.

• KIEAE Journal
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• v.3 no.2
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• pp.17-24
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• 2003

The purpose of this study is to present rational methods of multi-criteria optimization of the envelope of buildings. The object is to determine the optimum R-value of the envelope of a building, based on the following criteria: minimum building costs (including the cost of materials and construction) and yearly heating costs. Mathematical model described heat losses and gains in a building during the heating season. It takes into consideration heat losses through wall, roof, floor and windows. Particular attention was paid to have a more detailed description of heat gains due to solar radiation. On the assumption that shape of building is rectangle in order to solve the problem, optimum R-value of the envelope of a building is determined by using non-linear programing methods(Kuhn-Tucker Conditions). The results constitute information for designers on the optimum R-value of a building envelope for energy saving buildings.

• East Asian mathematical journal
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• v.29 no.3
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• pp.279-292
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• 2013

It is well known that each kernel function defines a primal-dual interior-point method(IPM). Most of polynomial-time interior-point algorithms for linear optimization(LO) are based on the logarithmic kernel function([2, 11]). In this paper we define a new eligible kernel function and propose a new search direction and proximity function based on this function for LO problems. We show that the new algorithm has ${\mathcal{O}}((log\;p){\sqrt{n}}\;log\;n\;log\;{\frac{n}{\epsilon}})$ and ${\mathcal{O}}((q\;log\;p)^{\frac{3}{2}}{\sqrt{n}}\;log\;{\frac{n}{\epsilon}})$ iteration bound for large- and small-update methods, respectively. These are currently the best known complexity results.

• Nuclear Engineering and Technology
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• v.43 no.4
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• pp.383-390
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• 2011

Nuclear power has become an essential part of electricity generation to meet the continuous growth of electricity demand. A Sodium-cooled Fast Reactor (SFR) was developed to extend uranium resource utilization under a growing nuclear energy scenario while concomitantly providing a nuclear waste management solution. Key questions in this scenario are when to introduce SFRs and how many reactors should be introduced. In this study, a methodology using Linear Programming is employed in order to quantify an optimized growth pattern of a nuclear energy system comprising light water reactors and SFRs. The optimization involves tradeoffs between SFR capital cost premiums and the total system U3O8 price premiums. Optimum nuclear growth patterns for several scenarios are presented, as well as sensitivity analyses of important input parameters.

• Honam Mathematical Journal
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• v.35 no.2
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• pp.235-249
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• 2013

It is well known that each kernel function defines primal-dual interior-point method (IPM). Most of polynomial-time interior-point algorithms for linear optimization (LO) are based on the logarithmic kernel function ([9]). In this paper we define new eligible kernel function and propose a new search direction and proximity function based on this function for LO problems. We show that the new algorithm has $\mathcal{O}(({\log}\;p)^{\frac{5}{2}}\sqrt{n}{\log}\;n\;{\log}\frac{n}{\epsilon})$ and $\mathcal{O}(q^{\frac{3}{2}}({\log}\;p)^3\sqrt{n}{\log}\;\frac{n}{\epsilon})$ iteration complexity for large- and small-update methods, respectively. These are currently the best known complexity results for such methods.

• Journal of Electrical Engineering and Technology
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• v.7 no.1
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• pp.34-45
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• 2012

In the present paper, the mover speed control of a linear induction motor (LIM) using a sliding mode control design is proposed, considering the end effects. First, the indirect field-oriented control LIM is derived, considering the end effects. The sliding mode control design is then investigated to achieve speed- and flux-tracking under load thrust force disturbance. The numerical simulation results of the proposed scheme present good performances in comparison to that of the classical sliding mode control.