• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.9
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• pp.1337-1346
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• 2015

In this paper, pattern classifier is designed to classify precipitation and non-precipitation events from weather radar data. The proposed classifier is based on Fuzzy Neural Network(FNN) and consists of three FNNs which operate in parallel. In the proposed network, the connection weights of the consequent part of fuzzy rules are expressed as two polynomial types such as constant or linear polynomial function, and their coefficients are learned by using Least Square Estimation(LSE). In addition, parametric as well as structural factors of the proposed classifier are optimized through Differential Evolution(DE) algorithm. After event classification between precipitation and non-precipitation echo, non-precipitation event is to get rid of all echo, while precipitation event including non-precipitation echo is to get rid of non-precipitation echo by classifier that is also based on Fuzzy Neural Network. Weather radar data obtained from meteorological office is to analysis and discuss performance of the proposed event and echo patter classifier, result of echo pattern classifier compare to QC(Quality Control) data obtained from meteorological office.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.7
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• pp.1114-1124
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• 2015

In this paper, precipitation / non-precipitation pattern classification of meteorological radar data is conducted by using neuro-fuzzy algorithm. Structure expression of meteorological radar data information is analyzed in order to effectively classify precipitation and non-precipitation. Also diverse input variables for designing pattern classifier could be considered by exploiting the quantitative as well as qualitative characteristic of meteorological radar data information and then each characteristic of input variables is analyzed. Preferred pattern classifier can be designed by essential input variables that give a decisive effect on output performance as well as model architecture. As the proposed model architecture, neuro-fuzzy algorithm is designed by using FCM-based radial basis function neural network(RBFNN). Two parts of classifiers such as instance classifier part and echo classifier part are designed and carried out serially in the entire system architecture. In the instance classifier part, the pattern classifier identifies between precipitation and non-precipitation data. In the echo classifier part, because precipitation data information identified by the instance classifier could partially involve non-precipitation data information, echo classifier is considered to classify between them. The performance of the proposed classifier is evaluated and analyzed when compared with existing QC method.

• Journal of Environmental Science International
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• v.4 no.5
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• pp.1-1
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• 1995

An attempt was made to study the subdivision of Korea by the annual amount and the annual change pattern of monthly precipitation days(that is one of the important elements of the precipitation characteristics), using the mean values for the years 1961-1990 at the 68 stations. The amplitudes of annual change were normalized and using these values, the principal component analysis was applied to determine the annual change patterns. The results show that they are expressed by the combinations of the three change patterns in almost whole regions of Korea. As a result,the annual change pattern of precipitation days in Korea is classified into 8 types from A to e,in detail, 36 types from A0 to e$\circled2$.And regional division of precipitation days in Korea is divided into 13 regions from I a to IIIC,into detail, 41 regions from I no to IIICl.

• Journal of Environmental Science International
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• v.4 no.5
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• pp.387-402
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• 1995

An attempt was made to study the subdivision of Korea by the annual amount and the annual change pattern of monthly precipitation days(that is one of the important elements of the precipitation characteristics), using the mean values for the years 1961-1990 at the 68 stations. The amplitudes of annual change were normalized and using these values, the principal component analysis was applied to determine the annual change patterns. The results show that they are expressed by the combinations of the three change patterns in almost whole regions of Korea. As a result, the annual change pattern of precipitation days in Korea is classified into 8 types from A to e, in detail, 36 types from A0 to e$\circled2$.And regional division of precipitation days in Korea is divided into 13 regions from I a to IIIC, into detail, 41 regions from I no to IIICl.

• The Journal of the Society of Stroke on Korean Medicine
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• v.9 no.1
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• pp.8-13
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• 2008

Objectives : This study was to investigated the correlation between average temperature & precipitation and pattern identification of the patients with stroke. Methods : 115 stroke patients within 30days of onset were registered during the study period. Pattern identification of stroke was classified into Fire and heat, Turbid phlegm and others. We took the mean of average temperature according to pattern identification and analyzed pattern identification into two groups according to climatological normal of average temperature in Seoul. We also analyzed pattern identification into two groups according to existence of precipitation. Results : Heat and fire, and other type of pattern identification had high frequency when average temperature was higher than 12.2℃. And there was no correlation between precipitation and pattern identification of stroke.

• Journal of Environmental Science International
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• v.4 no.4
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• pp.345-356
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• 1995

Examining the precipitation data collected during the period from 1960 to 1993, we found that Taegu Station represents an optimum station for explaining the interannual variations of the precipitation in Korea. Using the variations derived from Taegu, the secular trends of the precipitation in Korea have been studied. It was 삽so found that the interannual variations of summer monsoon precipitation are consistent with those of the annual precipitation. To explore the interannual variations of the summer monsoon precipitation, comparisons of the summer precipitation in Korea with that in China and Japan were made. The results of the empirical orthogonal function analysis showed that Korea, the Yangtze River and Huaihe River valley, and the south Japan are all located in the same climate system during summer. The detailed analysis was carried out on the comparison of the summer precipitation in Korea with that in the eastern part of the the mainland China. We found that the correlation pattern is similar to the East Asia/pacific pattern. The probable effects of the sea surface temperature on the precipitation in Korea were also discussed. Key Words : Precipitation in Korea, rainy seasons in East Asia, monsoon precipitation, interannual variations.

• Journal of Industrial Technology
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• v.21 no.B
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• pp.241-248
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• 2001

Normally at a flood season the operation of the dam depends on a short range weather forecast that makes many difficulties of the management at a dry season. It is needed to study the pattern of the long period rainfall. The concept of PMP(Probable Maximum Precipitation) was used for designing dam. From the concept, this study is applied the concept of monthly probable maximum precipitation for operating dam. It can be possible to let us know the appropriateness of a limiting water level at a rainy season. For the operation of dam at a dry season this study can predict roughly the flood season's pattern of precipitation by month or period, therfore the prediction of precipitation can rise efficient operation of a dam.

• Atmosphere
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• v.19 no.2
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• pp.199-211
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• 2009

In this paper, we examine the multiple change-point and change pattern in the 54 years (1954-2007) time series of the annual and the heavy precipitation characteristics (amount, days and intensity) averaged over South Korea. A Bayesian approach is used for detecting of mean and/or variance changes in a sequence of independent univariate normal observations. Using non-informative priors for the parameters, the Bayesian model selection is performed by the posterior probability through the intrinsic Bayes factor of Berger and Pericchi (1996). To investigate the significance of the changes in the precipitation characteristics between before and after the change-point, the posterior probability and 90% highest posterior density credible intervals are examined. The results showed that no significant changes have occurred in the annual precipitation characteristics (amount, days and intensity) and the heavy precipitation intensity. On the other hand, a statistically significant single change has occurred around 1996 or 1997 in the heavy precipitation days and amount. The heavy precipitation amount and days have increased after the change-point but no changes in the variances.

• Journal of Environmental Science International
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• v.8 no.3
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• pp.271-280
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• 1999

This study was carried out to investigate the characteristics of acidity in the precipitation and weather patterns that were influenced it at Kimhae area from March, 1992 to June, 1994. The range of pH value in the precipitation at Kimhae is 3.45 to 6.80 and the average is pH 4.62, and the major anion components associated with acidity in the precipitation are $Cl^-, SO_4^{-2}, NO_3^-$. These distributions are to be expected the influence of industrialization such as, urbanization and construction of industrial complex at Kimhae area and the long range trasporting of air pollutants from China. The weather patterns governing the acid rain at Kimhae were classified broadly into four types(Cyclone(type I-a, type I-b), Migratory Anticyclone(type II), Tropical Cyclone(type III), Siberia High(type IV) and weather pattern which had the most occurrence frequency of acid rain was type I-a and the average pH value of precipitation in this pattern was 4.45, and we are found that the source area of air mass which was accompanied with high acidic precipitation in Kimhae was the central China include with Peking through the analysis of surface weather maps, 850 hPa wind fields, and the streamline analyses.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.4
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• pp.424-433
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• 2021

Recent climate change has caused abnormal weather phenomena all over the world and a lot of damage in many fields of society. Particularly, a lot of recent damages were due to extreme precipitation, such as torrential downpour or drought. The objective of this study was to analyze the temporal and spatial changes in the precipitation pattern in South Korea. To achieve this objective, this study selected some of the precipitation indices suggested in previous studies to compare the temporal characteristics of precipitation induced by climate change. This study selected ten ASOS observatories of the Korea Meteorological Administration to understand the change over time for each location with considering regional distribution. This study also collected daily cumulative precipitation from 1951 to 2020 for each point. Additionally, this study generated high-resolution national daily precipitation distribution maps using an orographic precipitation model from 1981 to 2020 and analyzed them. Temporal analysis showed that although annual cumulative precipitation revealed an increasing trend from the past to the present. The number of precipitation days showed a decreasing trend at most observation points, but the number of torrential downpour days revealed an increasing trend. Spatially, the number of precipitation days and the number of torrential downpour days decreased in many areas over time, and this pattern was prominent in the central region. The precipitation pattern of South Korea can be summarized as the fewer precipitation days and larger daily precipitation over time.