• Proceedings of the KSME Conference
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• 2001.11b
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• pp.365-370
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• 2001

In order to minimize unstable flow occurred at a multiblade fan/scroll system, optimal angle and shape of cut-off was determined by using two-dimensional turbulent fluid field analyses and neural network. The results of CFD analyses were used for learning as data of input and output of neural network. After learning neural network optimization process was accomplished for design variables, the angle and the shape of cut-off, in the design domain. As a result of optimization, the optimal angle and shape were obtained as 71 and 0.092 times the outer diameter of impeller, respectively, which are very similar values to previous studies. Finally, it was verified that the fluid field is very stable for optimal angle and shape of cut-off by two-dimensional CFD analysis.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.7
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• pp.1104-1113
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• 2015

In this paper, we propose Two-Dimensional Robust Face Recognition System Realized with the Aid of Facial Symmetry with Illumination Variation. Preprocessing process is carried out to obtain mirror image which means new image rearranged by using difference between light and shade of right and left face based on a vertical axis of original face image. After image preprocessing, high dimensional image data is transformed to low-dimensional feature data through 2-directional and 2-dimensional Principal Component Analysis (2D)2PCA, which is one of dimensional reduction techniques. Polynomial-based Radial Basis Function Neural Network pattern classifier is used for face recognition. While FCM clustering is applied in the hidden layer, connection weights are defined as a linear polynomial function. In addition, the coefficients of linear function are learned through Weighted Least Square Estimation(WLSE). The Structural as well as parametric factors of the proposed classifier are optimized by using Particle Swarm Optimization(PSO). In the experiment, Yale B data is employed in order to confirm the advantage of the proposed methodology designed in the diverse illumination variation

• Smart Structures and Systems
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• v.15 no.3
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• pp.897-911
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• 2015

This study presents a novel approach based on advancements in Evolutionary Computation for data-driven modeling of complex multi-dimensional memory-dependent systems. The investigated example is a benchmark coupled three-dimensional system that incorporates 6 Bouc-Wen elements, and is subjected to external excitations at three points. The proposed technique of this research adapts Genetic Programming for discovering the optimum structure of the differential equation of an auxiliary variable associated with every specific degree-of-freedom of this system that integrates the imposed effect of vibrations at all other degrees-of-freedom. After the termination of the first phase of the optimization process, a system of differential equations is formed that represent the multi-dimensional hysteretic system. Then, the parameters of this system of differential equations are optimized in the second phase using Genetic Algorithms to yield accurate response estimates globally, because the separately obtained differential equations are coupled essentially, and their true performance can be assessed only when the entire system of coupled differential equations is solved. The resultant model after the second phase of optimization is a low-order low-complexity surrogate computational model that represents the investigated three-dimensional memory-dependent system. Hence, this research presents a promising data-driven modeling technique for obtaining optimized representative models for multi-dimensional hysteretic systems that yield reasonably accurate results, and can be generalized to many problems, in various fields, ranging from engineering to economics as well as biology.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.12
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• pp.5955-5977
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• 2018

Performance of the interpolation algorithm used in the technique of bi-dimensional empirical mode decomposition directly affects its popularization and application, so that the researchers pay more attention to the algorithm reasonable, accurate and fast. However, it has been a lack of an adaptive interpolation algorithm that is relatively satisfactory for the bi-dimensional empirical mode decomposition (BEMD) and is derived from the image characteristics. In view of this, this paper proposes an image interpolation algorithm based on the particle swarm and fractal. Its procedure includes: to analyze the given image by using the fractal brown function, to pick up the feature quantity from the image, and then to operate the adaptive image interpolation in terms of the obtained feature quantity. All parameters involved in the interpolation process are determined by using the particle swarm optimization algorithm. The presented interpolation algorithm can solve those problems of low efficiency and poor precision in the interpolation operation of bi-dimensional empirical mode decomposition and can also result in accurate and reliable bi-dimensional intrinsic modal functions with higher speed in the decomposition of the image. It lays the foundation for the further popularization and application of the bi-dimensional empirical mode decomposition algorithm.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2006.11a
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• pp.938-941
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• 2006

We present a new design method of one-dimensional multi-layered acoustic foams for transmission loss maximization by topology optimization. Multi-layered acoustic foam sequences consisting of acoustic air layers and poroelastic material layers are designed for target frequency values. For successful topology optimization design of multi-layered acoustic foams, the material interpolation concept of topology optimization is adopted. In doing so, an acoustic air layer is modeled as a limiting poroelastic material layer; acoustic air and poroelastic material are handled by a single set of governing equations based on Biot's theory. For efficient analysis of a specific multi-layered foam appearing during optimization, we do not solve the differential equations directly, but we use an efficient transfer matrix approach which can be derived from Biot's theory. Through some numerical case studies, the proposed design method for finding optimal multi-layer sequencing is validated.

• Progress in Medical Physics
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• v.11 no.1
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• pp.49-57
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• 2000

New method about the dose optimization problem in radiation treatment was researched. Since all conditions are more complex and there are more relevant variables, the solution of three-dimensional treatment planning is much more complicate than that of current two-dimensional one. There(ore, in this study, as a method to solve three-dimensional dose optimization problem, the considered variables was minized and researched by reducing the domain that solutions can exist and pre-determining the important beam parameters. First, the dangerous beam range that passes critical organ was found by coordinate transformation between linear accelerator coordinate and patient coordinate. And the beam size and rotation angle for rectangular collimator that conform tumor at arbitrary beam position was also determined. As a result, the available beam position could be reduced and the dependency on beam size and rotation angle, that is very important parameter in treatment planning, totally removed. Therefore, the resultant combinations of relevant variables could be greatly reduced and the dose optimization by objective function can be done with minimum variables. From the above results, the dose optimization problem was solved for the two-dimensional radiation treatment planning useful in clinic. The objective function was made by combination of dose gradient, critical organ dose and dose homogeniety. And the optimum variables were determined by applying step search method to objective function. From the dose distributions by optimum variables, the merit of new dose optimization method was verified and it can be implemented on commercial radiation treatment planning system with further research.

• Communications for Statistical Applications and Methods
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• v.4 no.1
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• pp.129-138
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• 1997

In this paper, the problem for choosing design points in the two dimensional case is condidered. In the one dimensional case, given the design density function, we can choose design points using the quantile function. However, in the two dimensional case, there is no clear definition of the percentile. Therefore, the idea of choosing design points in the univariate case can not be applied directly to the two dimensional case. We convert this problem into an optimization problem using the Voronoi diagram.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.10a
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• pp.902-907
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• 2004

In this paper, a multi-step optimization using a G.A. (Genetic Algorithm) with variable penalty function is introduced to the structural design optimization of a 5-head route machine. Our design procedure consist of two design optimization stage. The first stage of the design optimization is static design optimization. The following stage is dynamic design optimization stage. In the static optimization stage, the static compliance and weight of the structure are minimized simultaneously under some dimensional constraints and deflection limits. On the other hand, the dynamic compliance and the weight of the machine structure are minimized simultaneously in the dynamic design optimization stage. As the results, dynamic compliance of the 5-head router machine was decreased by about 37％ and the weight of the structure was decreased by 4.48％ respectively compared with the simplified structure model.

• Proceedings of the Korea Concrete Institute Conference
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• 2000.10a
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• pp.253-258
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• 2000

Recently, the area of design optimization, especially structural optimization, has been and to be a continuous active area of research. And the design optimizations of port facilities have been achieved by many other civil engineers. But the design optimization of port facilities were limited to the design optimization of the breasting dolphin. This paper invested the design optimization of mooring pier and the foundations of mooring pier was suggested considering the convenience of repair and reinforcement work. The mooring pier devised with prestressed precast concrete panel and rigid frame welded wide flange beam to steel pipe pile. To accomplish the design optimization of mooring pier, the Augmented Lagrangian Multiplier Method(ALM) of ADS(Garret N. Vanderplaats) optimization routine, BFGS method as optimizer and Golden Section Method as one dimensional search were utilized. As a result, thirty percent of material cost for construction was reduced by design optimization. The tensile stress of concrete panel and bottom flage was critical constraints under service load. So, using high strength concrete and steel will be economical. And lots of initial values must be invested to accomplish the design optimization in design procedures.

• 한국전산유체공학회:학술대회논문집
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• 2003.10a
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• pp.240-242
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• 2003

A method for performing two-dimensional lift-constraint drag minimization in inviscid compressible flows on unstructured meshes is developed. Sensitivities of objective function with respect to the design variables are efficiently obtained by using a continuous adjoint method. In addition, parallel algorithm is used in multi-point design optimization to enhance the computational efficiency. The characteristics of single-point and multi-point optimization are examined, and the comparison of these two method is presented.