• 한국멀티미디어학회논문지
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• 제6권2호
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• pp.247-258
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• 2003

얼굴인식 기술 분야에 있어서 Principal component analysis (PCA)기반 알고리즘은 많은 관련 알고리즘의 기초가 되고 있다. PCA는 매우 통계적인 접근이며 얼굴인식 분야에 응용하기 위해서는 많은 설계 결정요인 (design derision)을 필요로 한다. 본 논문에서는 일반적인 modular PCA알고리즘을 소개하면서 design decision을 얻는다. 얼굴인식 알고리즘 평가에 대한 표준 접근 방법인 September 1996 FERET evaluation protocol을 활용하여 각 모듈에 대한 서로 다른 구현방법을 실험하고 평가한다. 실험조건으로는 (1) 조도의 정규화 과정 을 변화 (2) JPEG과 wavelet compression 알고리즘 사용에 대한 성능효과를 분석 (3) 표현방법에서 eigenvectors의 수를 조절 (4) 분류과정에서 유사도 측정방법을 변경하는 등이다. 본 논문에서는 standard September 1996 FERET의 대용량 gallery image set에 대해 적용해 본 결과에 대해 정리하며, 100개의 무작위로 발생된 image set에 대해서도 알고리즘의 성능 변화를 평가한다.

• 한국전산구조공학회논문집
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• 제13권3호
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• pp.337-349
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• 2000

유전자 알고리즘(GA)은 어떠한 유형의 문제에도 적용가능하며 달리 방법이 없는 경우 최후의 수단으로 흔히 사용되는 방법이다. 강구조물 설계란 기본적으로 구조물을 이루는 부재로서 어떤 재료를 선택될 것인지를 결정하는 문제이다. 따라서 천문학적인 숫자의 설계가 존재하며 이들 중 최적의 설계를 탐색하는 것은 대체로 불가능한 일이다. 본 논문에서는 GA와 이와 관련된 여러 가지 기법들을 소개하고 강구조물 최적설계에 이들의 활용을 모색하였다. 작은 설계공간을 가지는 문제에서는 GA로 전역최적설계를 찾을 수 있었다. GA는 또한 연속변수 최적설계 문제에서도 최적설계를 찾았으며 구조물 최적설계에 적용될 수 있음을 보였다. 그러나 규모가 큰 현실문제에서는 GA가 최적 또는 최적에 근접한 설계를 항상 찾을 수 있을 것이라고 기대하기는 어려울 것으로 생각된다. GA에 G bit improvement를 추가하여 수행한 경우에 더 좋은 최적설계 결과를 보여주었으며 앞으로 이 부분의 연구가 활발해 질 것이다.

• Journal of Information Processing Systems
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• 제20권3호
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• pp.409-417
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• 2024

Excellent apparel design can increase market competitiveness. This article briefly introduced the theory of fractals and its application in the field of apparel design. The convolutional neural network (CNN) algorithm was used to assist in the evaluation of apparel designs. In the case analysis, the accuracy of the evaluation was validated by comparing the CNN algorithm with two other intelligent algorithms, support vector machine (SVM) and back propagation (BP). The evaluation of the proposed design showed that compared with SVM and BP algorithms, the CNN algorithm had higher accuracy in evaluating apparel designs. The evaluation result of the proposed apparel design not only further verifies the effectiveness of the CNN algorithm, but also demonstrates that the theory of fractals can be effectively applied in apparel design to provide more innovative designs.

• 대한전기학회논문지:시스템및제어부문D
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• 제49권11호
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• pp.599-609
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• 2000

The new design methodology of a hybrid fuzzy controller by means of the genetic algorithms is presented. First, a hybrid fuzzy controller(HFC) related to the optimal estimation of control parameters is proposed. The control input for the system in the HFC combined PID controller with fuzzy controller is a convex combination of the FLC's output and PID's output by a fuzzy variable, namely, membership function of weighting coefficient. Second, an auto-tuning algorithms utilizing the simplified reasoning method and genetic algorithms is presented to automatically improve the performance of hybrid fuzzy controller. Especially, in order to auto-tune scaling factors and PID parameters of HFC using GA, three kinds of estimation modes such as basic, contraction, and expansion mode are effectively utilized. The proposed HFC is evaluated and discussed to show applicability and superiority with the and of three representative processes.

• 한국정밀공학회지
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• 제14권12호
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• pp.24-29
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• 1997

Recently, Genetic Algorithm(GA), which is a stochastic direct search strategy that mimics the process of genetic evolution, is widely adapted into a search procedure for structural optimization. Contrast to traditional optimal design techniques which use design sensitivity analysis results, GA is very simple in their algorithms and there is no need of continuity of functions(or functionals) any more in GA. So, they can be easily applicable to wide area of design optimization problems. Also, owing to multi-point search procedure, they have higher porbability of convergence to global optimum compared to traditional techniques which take one-point search method. The methods consist of three genetics opera- tions named selection, crossover and mutation. In this study, a method of finding the omtimum size and topology of drilling machine is proposed by using the GA, For rapid converge to optimum, elitist survival model,roulette wheel selection with limited candidates, and multi-point shuffle cross-over method are adapted. And pseudo object function, which is the combined form of object function and penalty function, is used to include constraints into fitness function. GA shows good results of weight reducing effect and convergency in optimal design of drilling machine.

• Geomechanics and Engineering
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• 제24권3호
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• pp.237-251
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• 2021

The main purpose of this study is to investigate the performance of the proposed hybrid teaching-learning based optimization algorithm on the optimum design of reinforced concrete (RC) cantilever retaining walls. For this purpose, three different design examples are optimized with 100 independent runs considering continuous and discrete variables. In order to determine the algorithm performance, the optimization results were compared with the outcomes of the nine powerful meta-heuristic algorithms applied to this problem, previously: the big bang-big crunch (BB-BC), the biogeography based optimization (BBO), the flower pollination (FPA), the grey wolf optimization (GWO), the harmony search (HS), the particle swarm optimization (PSO), the teaching-learning based optimization (TLBO), the jaya (JA), and Rao-3 algorithms. Moreover, Rao-1 and Rao-2 algorithms are applied to this design problem for the first time. The objective function is defined as minimizing the total material and labor costs including concrete, steel, and formwork per unit length of the cantilever retaining walls subjected to the requirements of the American Concrete Institute (ACI 318-05). Furthermore, the effects of peak ground acceleration value on minimum total cost is investigated using various stem height, surcharge loads, and backfill slope angle. Finally, the most robust results were obtained by HTLBO with 50 populations. Consequently the optimization results show that, depending on the increase in PGA value, the optimum cost of RC cantilever retaining walls increases smoothly with the stem height but increases rapidly with the surcharge loads and backfill slope angle.

• 통합자연과학논문집
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• 제2권2호
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• pp.55-58
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• 2009

A ligand-receptor docking program is an indispensible tool in modern pharmaceutical design. An accurate prediction of small molecular docking pose to a receptor is essential in drug design as well as molecular recognition. An effective docking program requires the ability to locate a correct binding pose in a surprisingly complex conformational space. However, there is an inherent difficulty to predict correct binding pose. The odds are more demanding than finding a needle in a haystack. This mainly comes from the flexibility of both ligand and receptor. Because the searching space to consider is so vast, receptor rigidity has been often applied in docking programs. Even nowadays the receptor may not be considered to be fully flexible although there have been some progress in search algorithm. Improving the efficiency of searching algorithm is still in great demand to explore other applications areas with inherently flexible ligand and/or receptor. In addition to classical search algorithms such as molecular dynamics, Monte Carlo, genetic algorithm and simulated annealing, rather recent algorithms such as tabu search, stochastic tunneling, particle swarm optimizations were also found to be effective. A good search algorithm would require a good balance between exploration and exploitation. It would be a good strategy to combine algorithms already developed. This composite algorithms can be more effective than an individual search algorithms.

• 한국자동차공학회논문집
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• 제19권4호
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• pp.84-90
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• 2011

In active noise control filter, LMS algorithms which used for control filter, assure the convergence property, and computational burden of these algorithms are proportionate to the filter taps. The convergence speed of LMS algorithms is mainly determined by value of the convergence coefficient, so optimal selection of the value of convergence coefficient is very important. In this paper, We proposed novel adaptive fuzzy logic LMS algorithms with FIR filter structure which has better convergence speed and less computational burden than conventional LMS algorithms, for single channel active noise control with ill conditioned signal case. Computer simulations were performed to show the effectiveness of a proposed algorithms.

• 품질경영학회지
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• 제17권1호
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• pp.35-47
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• 1989

This paper is concerned with a development and evaluation of heuristic algorithms for the n-job, M-stage flowshop with sequence dependent setup times. Three heuristic algorithms, CAIDAN, DANNEN and PETROV, are proposed. The makespan is taken as a performance measure for the algorithms. The experiment for each algorithm is designed for a $4{\times}3{\times}3$ factorial design with 360 observations. The experimental factors are PS (ratio of processing times to setup times), M (number of machines), and N (number of jobs). The makespan of the proposed heuristic algorithms is compared with the optimal makespan obtained by the complete enumeration method. The result of comparision of performance measure is called a relative error. The mean relative errors of CAIDAN, DANNEN and PETROV algorithms are 4.488%. 6.712% and 7.282%, respectively. The computational results are analysed using SPSS. The experimental results show that the three factors are statistically signiticant at 5% level.

• Structural Engineering and Mechanics
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• 제86권2호
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• pp.197-209
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• 2023

In the case of designing control devices in a building, reliance on experimental formulation or engineering concepts without using optimization algorithms leads to non-optimal solutions or design parameters, which makes the use of control devices costly and unreasonable. The optimization algorithms are capable of identifying the required number of parameters for a specific design problem, however, this process is difficult and inefficient in dealing with some specific optimal design processes. This paper aims to introduce an upgraded version of the salp swarm algorithm to handle some engineering design. The performance of the new upgraded algorithm is tested using some benchmark test functions as well as a six-story benchmark building equipped with semi-active MR dampers. The simulation results show that the proposed algorithm can be successfully applied to get an optimal design of the MR dampers in the building.