• Journal of Mechanical Science and Technology
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• v.15 no.4
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• pp.413-421
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• 2001

A simple procedure to add and remove material simultaneously along the boundary is developed to optimize the shape of a two dimensional elastic problems and to minimize the maximum von Mises stress. The results for the two dimensional infinite plate with a hole, are close to the theoretical results of an elliptical boundary and the stress concentration is reduced by half for the fillet problem. The proposed shape optimization method, when compared with existing derivative based shape optimization methods has many features such as simplicity, applicability, flexibility, computational efficiency and a much better control on stresses on the design boundary.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 1999.10a
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• pp.323-335
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• 1999

In this paper, we propose a new hybrid model of artificial neural networks(ANNs) and genetic algorithm (GA) to optimal feature transformation and feature weighting. Previous research proposed several variants of hybrid ANNs and GA models including feature weighting, feature subset selection and network structure optimization. Among the vast majority of these studies, however, ANNs did not learn the patterns of data well, because they employed GA for simple use. In this study, we incorporate GA in a simultaneous manner to improve the learning and generalization ability of ANNs. In this study, GA plays role to optimize feature weighting and feature transformation simultaneously. Globally optimized feature weighting overcome the well-known limitations of gradient descent algorithm and globally optimized feature transformation also reduce the dimensionality of the feature space and eliminate irrelevant factors in modeling ANNs. By this procedure, we can improve the performance and enhance the generalisability of ANNs.

• Structural Engineering and Mechanics
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• v.58 no.3
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• pp.555-576
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• 2016

In this paper an efficient approach is introduced for design and analysis of double-layer grids including both geometrical and material nonlinearities, while the results are compared with those considering material nonlinearity. Optimum design procedure based on Enhanced Colliding Bodies Optimization method (ECBO) is applied to optimal design of two commonly used configurations of double-layer grids. Two ranges of spans as small and big sizes with certain bays of equal length in two directions are considered for each type of square grids. ECBO algorithm obtains minimum weight grid through appropriate selection of tube sections available in AISC Load and Resistance Factor Design (LRFD). Strength constraints of AISC-LRFD specifications and displacement constraints are imposed on these grids.

• Journal of Electrical Engineering and Technology
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• v.10 no.1
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• pp.188-194
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• 2015

This paper proposes a generalized regression neural network (GRNN) based algorithm for data interpolation and design optimization of brushless dc (BLDC) motor. The procedure makes use of magnet length, stator slot opening and air gap length as design variables. Cogging torque and average torque are treated as performance indices. The optimal design necessitates mitigating the cogging torque and maximizing the average torque by varying design variables. The data set for interpolation and ensuing design optimisation using GRNN is obtained by modeling a standard BLDC motor using finite element analysis (FEA) tool MagNet 7.1.1. The performance indices of the standard motor obtained using FEA are validated with an experimental model and an analytical method. The optimal design is authenticated using particle swarm optimization (PSO) algorithm and the performance indices of the optimal design obtained using GRNN is validated using FEA. The results indicate the suitability of GRNN as an interpolation and design optimization tool for a BLDC motor.

• Proceedings of the KSME Conference
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• 2001.06d
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• pp.286-291
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• 2001

This paper describes an optimal scheduling for ice slurry systems for energy cost saving. The optimization technique applied in the study is the dynamic programming method, for which the state variable is the storage in the ice storage tank and the control variable is the state of chiller's on-off switching. Though the costs during charge period is included in optimization by taking the average cost of ice per hour for slurry making, the time horizon for the simulation is limited building cooling period because accurate charge rate from the ice maker into the ice storage tank cannot be estimated during the charge period. In the operating simulation after optimizing procedure, energy consumption and operating cost for the optimal control are calculated and compared with them for a conventional control with one case of cooling load profile.

• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.3
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• pp.707-715
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• 1994

This study presents thickness optimization for the pressure vessel domes subject to internal pressure and axial force simultaneously. The considered typical pressure vessel domes are ellipsoidal and tori-spherical domes with skirt and nozzle part. These pressure vessel domes under loading have higher stress concentration on geometric discontinuity parts. Therefore, thickness optimization of axi-symmetric pressure vessel domes is essentially concerned on minimizing this stress concentration. The objective function is minimization of weight of pressure vessel dome. The design variable is thickness of dome and cylinder. Considered constraint is Von Mises equivalent stress. In the optimization procedure, ANSYS code is used. The equivalent and hoop stress of original shape domes are compared with those of optimal shape domes. And optimal thicknesses for pressure vessel domes are presented.

• Journal of the Korean Institute of Intelligent Systems
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• v.8 no.6
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• pp.106-118
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• 1998

The study concerns a design procedure of rule-based systems. The proposed rule-based fuzzy modeling implements system structure and parameter identification in the efficient from of "IF..., THEN..." statements, and exploits the theory of system optimization and fuzzy implication rules. The method for rule-based fuzzy modeling concerns the from of the conclusion part of the the rules that can be constant. Both triangular and Gaussian-like membership function are studied. The optimization hinges on an autotuning algorithm that covers as a modified constrained optimization method known as a complex method. The study introduces a weighted performance index (objective function) that helps achieve a sound balance between the quality of results produced for the training and testing set. This methodology sheds light on the role and impact of different parameters of the model on its performance. The study is illustrated with the aid of two representative numerical examples.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.3
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• pp.587-592
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• 2018

An adaptive beam forming system using a phased array antenna improves communication quality by beam forming adaptively to a communication environment having an interference signal. For adaptive beam forming, a good combination of the phases of the excited signals to each radiating element of the phased array antenna should be calculated. In this paper, improved particle swarm optimization algorithm that adds a re-spreading procedure according to particle density was proposed to increase the probability of good phase shift combination output.

• Journal of Korean Society of Water and Wastewater
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• v.22 no.1
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• pp.149-157
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• 2008

The reduction of leakage is a major issue of the South Korea water industry. The inclusion of pressure dependent leakage terms in network analysis allows the application of optimization techniques to identify the most effective means of reducing water leakage in distribution networks. This paper proposes a method to find optimal setting and location of control valve for reducing leakage efficiently. The proposed search method differs from previous methods for addressing optimal valve location problem and improves the GA simulation time with guaranteeing for getting the global optimal solution. The strength of this method has been demonstrated by means of case studies. This allows the procedure of optimization to be more robust and computational efficient.

• Journal of Power Electronics
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• v.4 no.3
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• pp.127-137
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• 2004

This paper introduces a hybrid induction motor control using a genetically optimized pseudo-on-line method. Optimization results from the use of a look-up table based on genetic algorithms to find the global optimum of an unconstrained optimization problem. The approach to induction motor control includes a pseudo-on-line procedure that optimally estimates parameters of a fuzzy PID (FPID) controller. The proposed hybrid genetic fuzzy PID (GFPID) controller is applied to speed control of a 3-phase induction motor and its computer simulation is carried out. Simulation results show that the proposed controller performs better than conventional FPID and PID controllers. The contribution of this paper is the introduction of a high performance hybrid form of induction motor control that makes on-line and real-time control of the drive system possible.