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의사결정나무모형을 이용한 노년기 주거유형선택 예측에 관한 연구 : 부산광역시 거주 베이비붐세대를 중심으로
최상일(Choi Sang-Il),박태진(Park Tae-Jin),강정규(Kang Jeong-Gyu) 한국주거환경학회 2011 주거환경(한국주거환경학회논문집) Vol.9 No.2
Nowaday, the domestic housing market environment is changing with economic, social, culture environment change. The main reason of the housing market change is that buyer's demands that is effected by buyer's awareness change, population composition change, and income increase is more and more diversify. Especially about 10 years later, when the baby boom generation, the huge population group would arrive at senescence, It could be expected the housing environment change is more dramatic. Because, baby boom generation is very different social/economic position, retirement preparation, values of house with other generations. This study would analyze the baby boom generation's housing selection trend in their senescence to show needs for this study. It should draw expectation model about house type and house size selection based on Extracting influence factors of housing selection for each variable. Result of this analysis, most of baby boom generation resided apartment house (apartment 68.4%, tenement house 12.2%, total 80.6%), also they will select various house style in their senescence (rural house 37.2%, tenement house 27.0%, second house 15.7%, detached house 12.8%) Abstract the house type selection expectation model, the most influenced factor is preparation for their retirement savings. Followed by current job, residential outlook of investment in senescence, house type at present, and thought about living with married children.
최상일(Sang-Il Choi) 한국컴퓨터정보학회 2015 韓國컴퓨터情報學會論文誌 Vol.20 No.11
We propose a hybrid pattern recognition method that effectively combines two different features for improving data classification. We first extract the PCA (Principal Component Analysis) and LDA (Linear Discriminant Analysis) features, both of which are widely used in pattern recognition, to construct a set of basic features, and then evaluate the separability of each basic feature. According to the results of evaluation, we select only the basic features that contain a large amount of discriminative information for construction of the combined features. The experimental results for the various data sets in the UCI machine learning repository show that using the proposed combined features give better recognition rates than when solely using the PCA or LDA features.
다양한 지역특징들의 결합 특징을 이용한 기체 분류 방법
최상일(Sang-Il Choi) 한국컴퓨터정보학회 2016 韓國컴퓨터情報學會論文誌 Vol.21 No.9
In this paper, we propose a gas classification method using combined features for an electronic nose system that performs well even when some loss occurs in measuring data samples. We first divide the entire measurement for a data sample into three local sections, which are the stabilization, exposure, and purge; local features are then extracted from each section. Based on the discrimination analysis, measurements of the discriminative information amounts are taken. Subsequently, the local features that have a large amount of discriminative information are chosen to compose the combined features together with the global features that extracted from the entire measurement section of the data sample. The experimental results show that the combined features by the proposed method gives better classification performance for a variety of volatile organic compound data than the other feature types, especially when there is data loss.
최상일(Choi Sang-Il),장현태(Jang Hyun Tae) 한국산학기술학회 2005 한국산학기술학회 학술대회 Vol.- No.-
공기중의 산소농축 PSA 기술로 RPSA(Rapid Pressure swing adsorption)이 적용되므로 1979년 이후 소형의 의료용 장치로 상업화되기 시작하였다. 산소발생기(산소농축기)의 경우에도 개량형 RPSA방식을 적용한 기술로써 최근 우리나라도 고령화 사회가 되므로써 의료용으로 사용이 확대되고 있으며, 기타 작업장이나 특수 시설 등에서 사용이 증대되고 있다. 이러한 산소농축기의 핵심부품 중의 하나인 흡착탑의 경우 흡착제 구성 및 흡착탑의 구조에 의하여 성능이 좌우되고 있다. 현재 상용화된 제올라이트의 각 흡착제의 흡착특성을 도출하기 위하여 압력, 온도, 수분함유량에 따른 파과곡선을 측정하여 흡착탑의 단수에 따른 최적 단수를 도출하였다.