• 정보처리학회논문지B
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• 제14B권5호
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• pp.377-382
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• 2007

본 논문에서는 방사 기저함수 네트워크의 파라미터를 전 영역에서 최적화하는 학습 알고리즘을 제안한다. 기존의 학습 알고리즘들은 지역 최적화만을 수행하기 때문에 성능의 한계가 있고 최종 결과가 초기 네트워크 파라미터 값에 크게 의존하는 단점이 있다. 본 논문에서 제안하는 하이브리드 모의 담금질 기법은 모의 담금질 기법의 전 영역 탐색 능력과 경사 기반 학습 알고리즘의 지역 최적화 능력을 조합하여 전 파라미터 영역에서 해를 찾을 수 있도록 한다. 제안하는 기법을 함수 근사화 문제에 적용하여 기존의 학습 알고리즘에 비해 더 좋은 학습 및 일반화 성능을 보이는 네트워크 파라미터를 찾을 수 있으며, 초기 파라미터 값의 영향을 크게 줄일 수 있음을 보인다.

• Physical Therapy Rehabilitation Science
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• 제12권2호
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• pp.140-148
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• 2023

Objective: Meniscal injuries are a common and high-risk condition among military personnel, leading to difficulties in performing missions.The objective of this study is to investigate the effects of combining electrical muscle stimulation therapy with exercise therapy during rehabilitation on pain, muscle strength, and function in patients after meniscectomy. Design: A two-group pretest-posttest design Methods: A total of 30 subjects were included in this study. They were randomly assigned to either the experimental group (n=15), which received knee extensor strengthening exercise along with electrical muscle stimulation, or the control group (n=15), which received only knee extensor strengthening exercise. Pre-test was conducted prior to the intervention, which consisted of 30 minutes of treatment five times a week for a total of 20 sessions. Post-test was performed after a 4-week period. Pain, strength, and function were assessed before and after the intervention. Results: The results of the study showed that there was a significant difference in pain reduction and muscle strength improvement in the experimental group, and a significant difference was also found between the experimental group and the control group in terms of functional evaluation. Conclusions: The combination of exercise therapy and electrical muscle stimulation therapy resulted in greater improvements in pain, strength, and function assessment, contributing to improved overall function.

• KIEE International Transaction on Electrical Machinery and Energy Conversion Systems
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• 제5B권3호
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• pp.262-266
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• 2005

In this paper, in order to enhance thrust of slotless type Permanent Magnet Linear Synchronous Motor, an optimal design is achieved by combining a genetic algorithm with 3D space harmonic method. In the case of multi-objective functions, the ratio of thrust/weight and thrust/volume are increased by $\7.56[%]l\;and\;7.98\[%]$, respectively. Thus, miniaturization and lightweight were realized at the same time.

• East Asian mathematical journal
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• 제17권1호
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• pp.129-133
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• 2001

The aim of this research note is to derive the well known Kummer's second theorem by transforming the integrals which represent some generalized hypergeometric functions. This theorem can also be shown by combining two known Bailey's and Preece's identities for the product of generalized hypergeometric series.

• 한국품질경영학회:학술대회논문집
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• 한국품질경영학회 1998년도 The 12th Asia Quality Management Symposium* Total Quality Management for Restoring Competitiveness
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• pp.610-621
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• 1998

In parameter design introduced by Taguchi, we analyze a signal-to-noise(SN) ratio. The SN ratio is a function of the expected loss due to the variation of quality characteristic. In this paper, an easy way for developing SN ratios is presented, which can be used to several quality characteristics simultaneously in parameter design. To develop such multivariate SN ratios, the transformation method of the expected loss and combining techniques are employed. And the analysis of real empirical data for an application of the proposed method is also presented.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2000년도 추계학술대회 학술발표 논문집
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• pp.115-118
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• 2000

In order to approximate a nonlinear function, modular wavelet networks combining wavelet theory and modular concept based on single layer neural network have been proposed as an alternative to conventional wavelet neural networks and kind of modular network. Modular wavelet networks provide better approximating performance than conventional one. In this paper, we propose an effective method to construct an optimal modualr wavelet network using genetic algorithm. This is verified through experimental results.

• Communications for Statistical Applications and Methods
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• 제19권1호
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• pp.129-134
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• 2012

In this paper we review a bi-aspect nonparametric test for the two-sample problem under the location translation model and propose a new one to accommodate a more broad class of underlying distributions. Then we compare the performance of our proposed test with other existing ones by obtaining empirical powers through a simulation study. Then we discuss some interesting features related to the bi-aspect test with a comment on a possible expansion for the proposed test as concluding remarks.

• 품질경영학회지
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• 제27권3호
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• pp.67-78
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• 1999

In parameter design introduced by Taguchi, we analyze a performance measure, so called SN ratio. The SN ratio is a function of the expected loss due to the variation of quality characteristic. In this paper, an easy way for developing performance measures is presented, which can be used to control several quality characteristics simultaneously in parameter design. To develop such multivariate performance measures, the transformation method of the expected loss and combining techniques are employed. And the analysis of real empirical data for an application of the proposed method is also presented.

• Journal of the Optical Society of Korea
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• 제16권1호
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• pp.70-75
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• 2012

An optimization methodology for designing a dielectric-filled plasmonic slot waveguide is presented. The genetic algorithm combined with a rigorous analysis based on the finite element method is used to optimize a nano-scaled plasmonic slot waveguide to have high mode confinement and a long propagation length, for which the objective function is defined as a figure of merit combining both propagation parameters.

• Journal of the Korean Data and Information Science Society
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• 제18권4호
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• pp.1145-1155
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• 2007

In this paper, we consider the permutation tests for the multivariate data under the two-sample problem setting. We review some testing procedures, which are parametric and nonparametric and compare them with the permutation ones. Then we consider to try to apply the permutation tests to the multivariate data having the continuous and discrete components together by choosing some suitable combining function through the partial testing. Finally we discuss more aspects for the permutation tests as concluding remarks.