• Proceedings of the Korea Water Resources Association Conference
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• 2005.05b
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• pp.766-770
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• 2005

Cascade-Correlation Neural Networks Model(CCNNM) is used to estimate daily evaporation using limited climatical variables such as atmospheric temperature, dewpoint temperature, relative humidity, wind speed, sunshine duration and radiation. DeBruln equation is applied to estimate daily free-surface evaporation. It is converted into pan evaporation using pan coefficient. The results of CCNNM shows better than those of Debruin equation. This research represents that the strong nonlinear relationship such as evaporation modeling can be generalized by the CCNNM ; a special type of Backpropagation algorithm Neural Networks Model.

• Proceedings of the Korea Water Resources Association Conference
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• 2006.05a
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• pp.115-119
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• 2006

The goal of this research is to develop and apply the generalized regression neural networks model (GRNNM) embedding genetic algorithm (GA) for pan evaporation, which is missed or ungaged and for the alfalfa reference evapotranspiration, which is not measured in South Korea. The GRNNM-GA is evaluated using the training, the testing, and reproduction performance respectively for the estimation of the PE and the alfalfa reference evapotranspiration. Since the observed data of the alfalfa reference evapotranspiration using lysimeter have not been measured for a long time in South Korea, the PM method is used to assume and estimate the observed alfalfa reference evapotranspiration. From this research, we evaluate the impact of the limited climatical variables on the accuracy of the GRNNM-GA. We should, furthermore, construct the credible data of the PE and the alfalfa reference evapotranspiration and suggest the reference data for irrigation and drainage networks system in South Korea.

• Journal of Physiology & Pathology in Korean Medicine
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• v.29 no.2
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• pp.127-132
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• 2015

In order to grasp the clear concepts and variables to treat Shanghan diseases which has complex meaning by each medical literature, several concepts and analytic method of structuralism from early to late stage encompassing Saussure and Derrida were used. Main concepts are langue and parole, signifiant and signifie, syntagme and paradigme, denotation and connotation, synchronie and diachronie, identity of structure and differance etc. and methods are substituting these concepts to historical Shanghan theories from Zhongjing to Ming-Qing dynasty and comparisons of synchronie about their era. Essential qualities of Shanghan diseases are pathologic phenomena under the order of unification of nature and man formed through concrescence between individual human body and geo-climatico-socio-cultural environmental conditions, neither injuries by cold pathogen nor five types of exopathogenic febrile diseases. The former environmental elements can be inferred from general traits of desires and public pathological aspects of social members, and the latter personal factors from corresponding features to those pathogenic variables. In addition, the concepts of Shanghan disease are added successively up to now via Jin-Yuan's four great masters and Wenbing masters, and thus the new concepts of denotation became another connotation obtaining new signifiant. In this way, for the treatment of Shanghan diseases, new theories should be made for ranging prescription over the wenbing field; reflecting not only climatical variables but also each patient's physio-pathological features and sociocultural variables. Thereby an appropriate and reasonable therapeutical systems can be designed and can guide research direction hereafter.

• Proceedings of the Korea Water Resources Association Conference
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• 2007.05a
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• pp.1423-1426
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• 2007

The goal of this research is to develop and apply the integrational model for the pan evaporation and the alfalfa reference evapotranspiration in Republic of Korea. Since the observed data of the alfalfa reference evapotranspiration using lysimeter have not been measured for a long time in Republic of Korea, PM method is used to assume and estimate the observed alfalfa reference evapotranspiration. The integrational model consists of staochastics and neural networks processes respectively. The stochastics process is applied to extend for the short-term monthly pan evaporation and alfalfa reference evapotranspiration. The extended data of the monthly pan evaporation and alfalfa reference evapotranspiration is used to evaluate for the training performance. For the neural networks process, the generalized regression neural networks model(GRNNM) is applied to evaluate for the testing performance using the observed data respectively. From this research, we evaluate the impact of the limited climatical variables on the accuracy of the integrational operation of stochastics and neural networks processes. We should, furthermore, construct the credible data of the pan evaporation and the alfalfa reference evapotranspiration, and suggest the reference data for irrigation and drainage networks system in Republic of Korea.

• Journal of Korean Society of Forest Science
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• v.106 no.1
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• pp.77-86
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• 2017

This study was conducted to analyze the relationship among climatic factors and radial growth of Pinus densiflora and Larix kaempferi in South Korea. To determine the climate-growth relationship, cluster analysis was applied to group surveyed regions by the climatical similarity, and a dendroclimatological model was developed to predict radial growth for each climate group under the RCP 4.5 and RCP 8.5 scenarios for greenhouse gases. The cluster analysis showed four climatic clusters (Cluster 1~4) from 10 regions for P. densiflora and L. kaempferi. The dendroclimatological model was developed through climatic variables and standardized residual chronology for each climatic cluster of P. densiflora and L. kaempferi. Four climatic variables were used in the models for P. densiflora ($R^2$ values between 0.38 to 0.58). Two to five climatic variables were used in the models for L. kaempferi ($R^2$ values between 0.31 to 0.43). The growth simulations with two RCP climate-change scenarios(RCP 4.5 and RCP 8.5) were used for growth prediction. The radial growth of the Cluster 4 of P. densiflora, the mountainous region at high elevation, tend to increase, while those of cluster 2 and 3 of P. densiflora, the region of the hightest average temperature, tends to decrease. The radial growth of the Cluster 1 of L. kaempferi the region of the lowest minimum temperature, while that of Cluster 2, the region of the highest average temperature, tends to decrease. The radial growth of Cluster 3 of L. kaempferi, the region in the east coast and Cluster 4, the region at high elevation, tends to hold steady. The results of this study are expected to provide valuable information necessary for predicting changes in radial growth of Pinus densiflora and Larix kaempferi caused by climate change.