KLI

推計學的 Modelling에 必要한 合成資料의 發生

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Alternative Title
Generation of Synthetic Data for Stochastic Modelling in Water Pollution Control
Abstract
대기온도, 수온 같은 時系別을 推計學的으로 분석함으로써 자료를 합성할 수 있는 模擬發生모델을 시도하였다. 周期成分은 Fourier급수 형태로 표시하였고, 推計學的成分은 1차 Markov모델로 나타내었다. 일반적으로 수온자료는 희귀하거나 단기인 것이 보통인데 대기온도와 수온과의 관계를 이용하여도 수온을 발생시킬 수 있을 것이다.
This paper presents a model for synthesising daily average air temperature and water temperature data. Periodic components are descreied by the Foorier series and stochastic somponents are produced using a first order Markov model. A cross correlation model can be used to generate water temperatures, providing correlation coefficient is high.
This paper presents a model for synthesising daily average air temperature and water temperature data. Periodic components are descreied by the Foorier series and stochastic somponents are produced using a first order Markov model. A cross correlation model can be used to generate water temperatures, providing correlation coefficient is high.
Author(s)
柳明辰金聲得黃成一
Issued Date
1977
Type
Research Laboratory
URI
https://oak.ulsan.ac.kr/handle/2021.oak/4786
http://ulsan.dcollection.net/jsp/common/DcLoOrgPer.jsp?sItemId=000002024882
Alternative Author(s)
Yu, Myung-JinKim, Seong-DeukHwang,Sung-Il
Publisher
연구논문집
Language
kor
Rights
울산대학교 저작물은 저작권에 의해 보호받습니다.
Citation Volume
8
Citation Number
2
Citation Start Page
37
Citation End Page
44
Appears in Collections:
Research Laboratory > University of Ulsan Report
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