• 반도체디스플레이기술학회지
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• 제10권3호
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• pp.75-81
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• 2011

This paper presents a novel method for image classification based on a hybrid genetic algorithm (GA) and support vector machine (SVM) approach which can significantly improve the classification performance for content-based image retrieval (CBIR). Though SVM has been widely applied to CBIR, it has some problems such as the kernel parameters setting and feature subset selection of SVM which impact the classification accuracy in the learning process. This study aims at simultaneously optimizing the parameters of SVM and feature subset without degrading the classification accuracy of SVM using GA for CBIR. Using the hybrid GA and SVM model, we can classify more images in the database effectively. Experiments were carried out on a large-size database of images and experiment results show that the classification accuracy of conventional SVM may be improved significantly by using the proposed model. We also found that the proposed model outperformed all the other models such as neural network and typical SVM models.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 2000년도 추계정기학술대회:지능형기술과 CRM
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• pp.417-426
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• 2000

This study suggests integrated neural network models for Interest rate forecasting using change-point detection, classifiers, and classification functions based on structural change. The proposed model is composed of three phases with tee-staged learning. The first phase is to detect successive and appropriate structural changes in interest rare dataset. The second phase is to forecast change-point group with classifiers (discriminant analysis, logistic regression, and backpropagation neural networks) and their. combined classification functions. The fecal phase is to forecast the interest rate with backpropagation neural networks. We propose some classification functions to overcome the problems of two-staged learning that cannot measure the performance of the first learning. Subsequently, we compare the structured models with a neural network model alone and, in addition, determine which of classifiers and classification functions can perform better. This article then examines the predictability of the proposed classification functions for interest rate forecasting using structural change.

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2009년도 춘계 학술논문 발표대회 학계
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• pp.253-257
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• 2009

General technique and management technology of agriculture have development in every year to ensure the competitiveness of agriculture. Accordingly, Interested in using information systems management technology is improving. For information system, the first system of rural buildings category should be established. Classification system is set up through each specific code. and it takes advantage of the information system is to achieve the computerization of agricultural society. Therefore, in this study construction information classification system, quantity of output category, got to the standard classification system architecture, apply to agricultural buildings to review the situation and saw a problem. The result, it is the complexity and broad scope, and it is set to inappropriate setting of the Category item.

• 한국IT서비스학회지
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• 제18권5호
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• pp.17-30
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• 2019

With the advent of the Fourth Industrial Revolution, virtual reality, a technology that has recently attracted attention, is emerging as a core technology that will lead the future industry by changing the paradigm of various industries. The development of 3D rendering, computer graphics, and mobile technologies enabled the development of various smart devices and led to the popularization of virtual reality services using them. Recently, with the development of virtual reality-related technology, various devices and contents such as VR-related HMDs are being developed and released. However, since the classification for VR technology has not yet been established, it is difficult to define a range of industries and services to which VR can be applied. Therefore, in this study proposes a service classification system in terms of industries that can apply VR technology and services that can be provided based on the studies on industries and services of VR technology related to the Fourth Industrial Revolution. VR's industrial classification consists of eight industries including entertainment, media, education, medical care, architecture, manufacturing, distribution, tourism and each service is divided into two service categories and composed 16 services. Through the collection and analysis of virtual reality service cases, the service distribution and characteristics of each industry can be analyzed. In addition, we can develop a virtual reality new business model and present a service case for the intersecting areas. This study is expected to be used as a basic research for the activation of virtual reality services in the future.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2005년도 학술발표회(2)
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• pp.1138-1140
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• 2005

• 한국전자거래학회지
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• 제8권3호
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• pp.219-239
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• 2003

전자상거래 요소기술들에 기반 한 글로벌 디지털 경제가 급속하게 확산되고 있다. 본 연구에서는 전자상거래에 관련된 주요요소기술들을 체계적으로 분류하기 위한 전자상거래 기술분류 모형을 개발하였다. 또한 본 연구에서는 전자상거래 기술분류 모형이 어떻게 활용될 수 있는 지에 대한 구체적인 방안도 제시하였다. 본 논문에서 제시한 전자상거래 기술분류 모형은 전자상거래에 관련된 주요 요소기술 상호간의 연관관계나 응용에 대한 체계적인 분석이 가능하며 향후 전자상거래와 디지털 경제에 관련된 연구의 주요한 지침으로 활용될 수 있을 것이다.

• 기술혁신학회지
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• 제9권3호
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• pp.496-513
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• 2006

과학기술부는 국가 과학기술정보의 체계적인 수집, 분석 및 배포를 위해 국가차원에서 국가과학기술종합정보시스템(NTIS)을 구축하고 있다. 성공적인 NTIS의 추진을 위해서는 다양한 정보를 체계적으로 분류하고 유통시킬 수 있는 분류체계가 필요하다. 본 논문에서는 현재의 국가과학기술표준분류와 각 기관의 분류를 상호 연계하는 호환표를 사용하여 NTIS를 구축하는 것이 타당한지에 대하여 분석하였다. 분석결과 현행 분류체계를 이용하는 경우 정보의 유통이 원활하지 못한 것으로 나타나고 있으므로 성공적인 NTIS의 구축을 위해서는 새로운 분류체계가 고려될 필요가 있는 것으로 보인다.

• Computers and Concrete
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• 제20권1호
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• pp.23-29
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• 2017

In this study engineered steel fibres used as reinforcement for concrete were characterized by number of key mechanical and spatial parameters, which are easy to measure and quantify. Such commonly used parameters as length, diameter, fibre intrinsic efficiency ratio (FIER), hook geometry, tensile strength and ductility were considered. Effective classification of various fibres was demonstrated using simple multivariate computations involving principal component analysis (PCA). Contrary to univariate data mining approach, the proposed analysis can be efficiently adapted for fast, robust and direct classification of engineered steel fibres. The results have revealed that in case of particular spatial/geometrical conditions of steel fibres investigated the FIER parameter can be efficiently replaced by a simple aspect ratio. There is also a need of finding new parameters describing properties of steel fibre more precisely.

• Journal of information and communication convergence engineering
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• 제17권1호
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• pp.14-20
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• 2019

Currently, microarray gene expression data take advantage of the sufficient classification of cancers, which addresses the problems relating to cancer causes and treatment regimens. However, the sample size of gene expression data is often restricted, because the price of microarray technology on studies in humans is high. We propose enhancing the gene expression classification of support vector machines with generative adversarial networks (GAN-SVMs). A GAN that generates new data from original training datasets was implemented. The GAN was used in conjunction with nonlinear SVMs that efficiently classify gene expression data. Numerical test results on 20 low-sample-size and very high-dimensional microarray gene expression datasets from the Kent Ridge Biomedical and Array Expression repositories indicate that the model is more accurate than state-of-the-art classifying models.

• 충청수학회지
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• 제25권4호
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• pp.633-642
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• 2012

We give the complete classification of binary formally self-dual even codes of length 18. There are exactly 26568 inequivalent such codes. This completes the classification of binary formally self-dual even codes of length up to 18.