• Journal of Radiation Protection and Research
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• 제14권1호
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• pp.71-74
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• 1989

최소자승법을 써서 우리 학회의 연차별 회원수와 학회지 게재 논문 편수와의 상관 관계식을 구하고, 그 결과로 부터 연간 4회까지 학회지를 발간코자 할 때의 필요 회원수를 추정한 바 최소한 650여명의 회원수를 확보해야만 할 것으로 보였다.

• 한국태양에너지학회 논문집
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• 제29권4호
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• pp.15-21
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• 2009

Since the solar radiation is main input for sizing any solar photovoltaic system and solar thermal power system, it will be necessary to understand and evaluate the insolation data. The Korea Institute of Energy Research(KIER) has begun collecting horizontal global insolation data since May, 1982 and direct normal insolation data since December 1992 at 16 different locations. Because of a poor reliability of existing data, KIER's new data will be extensively used by solar energy system users as well as by research institutes. Among some significant results, the yearly averaged horizontal global insolation was turned out 3.60 kWh/$m^2$/day and the yearly mean 2.62 kWh/$m^2$/day of the direct normal insolation was evaluated for all days.

• 설비공학논문집
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• 제14권11호
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• pp.897-906
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• 2002

Standard temperature and absolute humidity weather correlations of Seoul for dynamic energy simulation have been developed regressing the measured data compiled by the Korea Meteorological Adminstration during a 10-year period from 1991 to 2000. The mathematical equations can generate the daily and yearly variations of outdoor weather data with consistency unlike the measured data which may show abnormal behavior, Considering that each hour of the day follows a certain yearly pattern, the correlations are developed for each hour. The derived 24 simple mathematical equations can be used for estimating outdoor temperature and humidity conditions for any arbitrary time of the year.

• 한국태양에너지학회 논문집
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• 제31권1호
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• pp.87-92
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• 2011

Since the atmospheric clearness index is main factor for evaluating atmosphere environment, it is necessary to estimate its characteristics all over the major cities in Korea. We have begun collecting clearness index data since 1982 at 16 different cities and considerable effort has been made for constructing a standard value from measured data at each city. The new clearness data will be extensively used by evaluating atmospheric environment as well as by solar application system designer or users. Yearly mean 64% of the atmospheric clearness index was evaluated for clear day all over, and significant difference of horizontal global insolation is observed between 1982~1986 and 1987~1991, 1992~1996, 1997~2001, 2002~2009 through 16 different cities in Korea.

• 한국군사과학기술학회지
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• 제18권1호
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• pp.55-65
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• 2015

This paper describes the results of a temperature analysis of Korea and its neighbor regions for temperature specification of weapon systems to be deployed in Korea, and introduces the concept of a standard deviation frequency of occurrence which represents a frequency of yearly occurrence. On the basis of this analysis, reasonable operational temperatures for the Korea weapon systems are recommended, and the regional frequency of yearly occurrence of temperatures worse than recommended operational temperatures in each country regions are presented.

• International Journal of Air-Conditioning and Refrigeration
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• 제11권4호
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• pp.199-208
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• 2003

Standard temperature and absolute humidity weather data correlations of Seoul for dynamic energy simulation have been developed regressing the measured data compiled by the Korea Meteorological Adminstration during a l0-year period from 1991 to 2000. The mathematical equations can generate consistent daily and yearly variations of outdoor weather data unlike the measured data which may show abnormal behavior. Considering that each hour of the day follows a certain yearly pattern, 24 correlations are developed for each hour of the day. The derived simple mathematical equations can be used for estimating outdoor temperature and humidity conditions for any arbitrary time of the year.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2010년도 학술발표회
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• pp.1645-1648
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• 2010

The goal of this research is to apply the neural networks model for the disaggregation of the pan evaporation (PE) data, Republic of Korea. The neural networks model consists of recurrent neural networks model (RNNM). The disaggregation means that the yearly PE data divides into the monthly PE data. And, for the performances of the neural networks model, it is composed of training and test performances, respectively. The training and test performances consist of the historic, the generated, and the mixed data, respectively. From this research, we evaluate the impact of RNNM for the disaggregation of the nonlinear time series data. We should, furthermore, construct the credible data of the monthly PE from the disaggregation of the yearly PE data, and can suggest the methodology for the irrigation and drainage networks system.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2010년도 학술발표회
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• pp.1560-1563
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• 2010

The goal of this research is to apply the neural networks model for the disaggregation of the pan evaporation (PE) data, Republic of Korea. The neural networks model consists of support vector machine neural networks model (SVM-NNM). The disaggregation means that the yearly PE data divides into the monthly PE data. And, for the performances of the neural networks model, it is composed of training and test performances, respectively. The training and test performances consist of the historic, the generated, and the mixed data, respectively. From this research, we evaluate the impact of SVM-NNM for the disaggregation of the nonlinear time series data. We should, furthermore, construct the credible data of the monthly PE from the disaggregation of the yearly PE data, and can suggest the methodology for the irrigation and drainage networks system.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2010년도 학술발표회
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• pp.1346-1349
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• 2010

The goal of this research is to apply the neural networks models for the disaggregation of the pan evaporation (PE) data, Republic of Korea. The neural networks models consist of generalized regression neural networks model (GRNNM) and multilayer perceptron neural networks model (MLP-NNM), respectively. The disaggregation means that the yearly PE data divides into the monthly PE data. And, for the performances of the neural networks models, they are composed of training and test performances, respectively. The training and test performances consist of the historic, the generated, and the mixed data, respectively. From this research, we evaluate the impact of GRNNM and MLP-NNM for the disaggregation of the nonlinear time series data. We should, furthermore, construct the credible data of the monthly PE from the disaggregation of the yearly PE data, and can suggest the methodology for the irrigation and drainage networks system.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2015년도 학술발표회
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• pp.488-488
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• 2015

Intermittent streamflow is common phenomenon in arid and semi-arid regions. To manage water resources of intermittent streamflows, stochactic simulation data is essential; however the seasonally stochastic modeling for intermittent streamflow is a difficult task. In this study, using the periodic Markov chain model, we simulate intermittent monthly streamflow for occurrence and the periodic gamma autoregressive and copula models for amount. The copula models were tested in a previous study for the simulation of yearly streamflow, resulting in successful replication of the key and operational statistics of historical data; however, the copula models have never been tested on a monthly time scale. The intermittent models were applied to the Colorado River system in the present study. A few drawbacks of the PGAR model were identified, such as significant underestimation of minimum values on an aggregated yearly time scale and restrictions of the parameter boundaries. Conversely, the copula models do not present such drawbacks but show feasible reproduction of key and operational statistics. We concluded that the periodic Markov chain based the copula models is a practicable method to simulate intermittent monthly streamflow time series.