• 제목/요약/키워드: Abstract Data

검색결과 484건 처리시간 0.049초

A Novel Simple Method to Abstract the Entire Parameters of the Solar Cell

  • Park, Minwon;Yu, In-Keun
    • KIEE International Transaction on Electrical Machinery and Energy Conversion Systems
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    • 제4B권2호
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    • pp.86-91
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    • 2004

  • PV power generation, which directly converts solar radiation into electricity, contains numerous significant advantages. It is inexhaustible and pollution-free, silent, contains no rotating parts, and has size-independent electricity conversion efficiency. The positive environmental effect of photovoltaics is that it replaces the more polluting methods of electricity generation or that it provides electricity where none was available before. This paper highlights a novel simple method to abstract the entire parameters of the solar cell. In development, design and operation of PV power generation systems, a technique for constructing V-I curves under different levels of solar irradiance and cell temperature conditions using basic characteristic values of the PV module is required. Everyone who has performed manual acquisition and analysis of solar cell I versus V data would agree that the job is tedious and time-consuming. A better alternative is to use an automated curve tracer to print out the I versus V curves and compute the four major parameters; $V_{oc}$, $I_{sc}$, FF, and . Generally, the V-I curve tracer indicates only the commonly used solar cell parameters. However, with the conventional V-I curve tracer it is almost impossible to abstract the more detailed parameters of the solar cell; A, $R_{s}$ and $R_{sh}$ , which satisfies the user, who aims at the analysis of the development of the PV power generation system, that being advanced simulation. In this paper, the proposed method provides us with satisfactory results to enable us to abstract the detailed parameters of the solar cell; A, $R_s$ and $R_{sh}$.>.

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머신러닝을 이용한 웹페이지 내의 특정 정보 추출 (Extracting Specific Information in Web Pages Using Machine Learning)

  • 이정윤;김재곤
    • 산업경영시스템학회지
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    • 제41권4호
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    • pp.189-195
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    • 2018

  • With the advent of the digital age, production and distribution of web pages has been exploding. Internet users frequently need to extract specific information they want from these vast web pages. However, it takes lots of time and effort for users to find a specific information in many web pages. While search engines that are commonly used provide users with web pages containing the information they are looking for on the Internet, additional time and efforts are required to find the specific information among extensive search results. Therefore, it is necessary to develop algorithms that can automatically extract specific information in web pages. Every year, thousands of international conference are held all over the world. Each international conference has a website and provides general information for the conference such as the date of the event, the venue, greeting, the abstract submission deadline for a paper, the date of the registration, etc. It is not easy for researchers to catch the abstract submission deadline quickly because it is displayed in various formats from conference to conference and frequently updated. This study focuses on the issue of extracting abstract submission deadlines from International conference websites. In this study, we use three machine learning models such as SVM, decision trees, and artificial neural network to develop algorithms to extract an abstract submission deadline in an international conference website. Performances of the suggested algorithms are evaluated using 2,200 conference websites.

  • https://doi.org/10.11627/jkise.2018.41.4.189 인용 PDF KSCI

Ionosphere Modeling and Estimation using Regional GPS Data

  • Yoola Hwang;Park, Kwan-Dong;Lim, Hyung-Chul;Joh, Jeong-Ho;Park, Pil-Ho
    • 한국우주과학회:학술대회논문집(한국우주과학회보)
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    • 한국우주과학회 2003년도 한국우주과학회보 제12권1호
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    • pp.50-50
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    • 2003

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