• Journal of Korea Water Resources Association
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• v.51 no.11
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• pp.1031-1041
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• 2018

ANFIS-based methodology for improving GloSea5 ensemble weather forecast is developed and evaluated in this study. The proposed method consists of two steps: pre & post processing. For ensemble prediction of GloSea5, weights are assigned to the ensemble members based on Optimal Weighting Method (OWM) in the pre-processing. Then, the bias of the results of pre-processed is corrected based on Model Output Statistics (MOS) method in the post-processing. The watershed of the Chungju multi-purpose dam in South Korea is selected as a study area. The results of evaluation indicated that the pre-processing step (CASE1), the post-processing step (CASE2), pre & post processing step (CASE3) results were significantly improved than the original GloSea5 bias correction (BC_GS5). Correction performance is better the order of CASE3, CASE1, CASE2. Also, the accuracy of pre-processing was improved during the season with high variability of precipitation. The post-processing step reduced the error that could not be smoothed by pre-processing step. It could be concluded that this methodology improved the ability of GloSea5 ensemble weather forecast by using ANFIS, especially, for the summer season with high variability of precipitation when applied both pre- and post-processing steps.

• Journal of Korea Water Resources Association
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• v.49 no.1
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• pp.61-72
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• 2016

In Korea, the aquifers at the coastal areas are mostly shallow alluvial unconfined aquifers. To simulate the flow and dispersion in unconfined aquifer, a FDM model has been developed to solve the nonlinear Boussinesq equation. Related analysis and verification have been executed. The iteration method is used to solve the nonlinearity, and the model shows 3-D shape because it is a 2-D y model that consider the undulation of water table and bottom. For the verification of the model, the output of flow module is compared to the 1-D analytic solution of Lee (1989) which have the drawdown or uplift boundary condition, and the two results show almost the same value. and the mass balance of dispersion module shows about 10% error. The developed model can be used for the analysis and design of the flow and dispersion in the unconfined aquifers. The model has been applied to the estuary area of Ssangcheon watershed, and the parameters have been deduced as a result : hydraulic conductivity is 90 m/day, and longitudinal dispersivity is 15 m. And the analysis with these parameters shows that the wells are situated in the influence circle of each others except for No. 7 well. Groundwater discharge to sea is $3700m^3/day$. And the chlorine ion ($cl^-$) concentration at the pumping wells increase at least 1000 mg/L if groundwater dam is not exist, so the groundwater dam plays an important role for the prevention of sea water intrusion.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.9
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• pp.526-535
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• 2018

Recently, in order to reduce the $CO_2$ emission in the island area, countermeasures to operate power system in a stable manner are being researched due to decrease of the operation rate in diesel generators and the increase of renewable energy sources. The phenomenon of energy sinking can be occurred if the output of renewable energy sources is larger than customer loads. Voltage of CVCF(constant voltage & constant frequency) battery could be increased rapidly according to the condition of SOC(state of charge) and blackout could be occurred due to shut-down of CVCF inverter, at carbon free island micro-grid based on the CVCF inverter. In order to overcome these problems, this paper proposes a transient operation algorithm in CVCF based micro-grid which in advance prevents shut-down of CVCF inverter during the energy sinking. And also this paper proposes the modeling of micro-grid including CVCF inverter, PV system, customer load using PSCAD/EMTDC S/W. From the results of micro-grid modeling based on the proposed algorithm, it is confirmed that CVCF based micro-grid can properly prevent shut-down of CVCF inverter according to SOC and battery voltage of CVCF inverter when energy sinking is occurred.

• Journal of the Korean Association of Geographic Information Studies
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• v.13 no.3
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• pp.74-90
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• 2010

The objectives of this paper are to introduce the GIS based resource circulation information, and to identify additional(or potential) industrial symbiosis based on existing industrial symbiosis and linkage-pair of industry by material. The resource circulation information contains information of the reuse of materials, water, and energy for all manufacturing companies in Ulsan Metropolitan City. The information can further be classified into the three steps -- input information(raw materials), flow information (products), and output information (by-products). The survey data from 3,768 industries and institutions in Ulsan Metropolitan area were collected and built into the GIS to analyze the mechanism of the industrial symbiosis. The results of this study strongly suggest that there are some additional industrial symbioses using by-products(materials, steam, waste water) and further efforts should be given to make them more effective. We expect that the methodology of building the resource circulation information of this study can be helpful to other local governments that try to build similar system.

• Journal of the Korean Society of Radiology
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• v.3 no.1
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• pp.29-39
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• 2009

In this paper has proposed to the recognition of the disease on medical images using neural network. The neural network is constructed as three-layers of the input-layer, the hidden-layer and the output-layer. The training method applied for the recognition of disease region is adaptive error back-propagation. The low-frequency region analyzed by DWT are expressed by matrix. The coefficient-values of the characteristic polynomial applied are n+1. The normalized maximum value +1 and minimum value -1 in the range of tangent-sigmoid transfer function are applied to be use as the input vector of the neural network. To prove the validity of the proposed methods used in the experiment with a simulation experiment, the input medical image recognition rate the evaluation of areas of disease. As a result of the experiment, the characteristic polynomial coefficient of low-frequency area matrix, conversed to 4 level DWT, was proved to be optimum to be applied to the feature parameter. As for the number of training, it was marked fewest in 0.01 of learning coefficient and 0.95 of momentum, when the adaptive error back-propagation was learned by inputting standardized feature parameter into organized neural network. As to the training result when the learning coefficient was 0.01, and momentum was 0.95, it was 100% recognized in fifty-five times of the stomach image, fifty-five times of the chest image, forty-six times of the CT image, fifty-five times of ultrasonogram, and one hundred fifty-seven times of angiogram.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.6 no.4
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• pp.283-296
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• 2008

The numerical simulations for groundwater flow were carried out to support the input parameters for safety assessment in LILW repository site. As the input parameters for safety assessment, the groundwater flux into the underground facilities during construction, flow rate through the disposal silo after closure of disposal silo and flow pathway from the disposal silo to discharge area were analyzed using the 10 cases groundwater flow simulations. From the total 10 numerical simulation results, the statistics of estimated output were similar to among 10 cases. In some cases, the analyzed input parameters were strongly governed by locally existed high permeable fracture zone at radioactive waste disposed depth. Indeed, numerical simulation for well scenario as a human intrusion scenario was carried out using the hydraulically severe case model. Using the results of well scenario, the input parameters for safety assessment were also obtained through the numerical simulation.

• The Journal of Engineering Geology
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• v.15 no.1
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• pp.67-76
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• 2005

This paper presents the application of a neural network for prediction of the unconfined compressive strength from physical properties and schmidt hardness number on rock samples. To investigate the suitability of this approach, the results of analysis using a neural network are compared to predictions obtained by statistical relations. The data sets containing 55 rock sample records which are composed of sandstone and shale were assembled in Daegu area. They were used to learn the neural network model with the back-propagation teaming algorithm. The rock characteristics as the teaming input of the neural network are: schmidt hardness number, specific gravity, absorption, porosity, p-wave velocity and S-wave velocity, while the corresponding unconfined compressive strength value functions as the teaming output of the neural network. A data set containing 45 test results was used to train the networks with the back-propagation teaming algorithm. Another data set of 10 test results was used to validate the generalization and prediction capabilities of the neural network.

• Korean Journal of Ecology and Environment
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• v.33 no.1 s.89
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• pp.31-37
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• 2000

For the purpose of surveying the physicochemical composition of sediment collected from Kwangyang Bay, the percentage of water loss, COD, $H_2S$, grain size and 10 heavy metals were studied at 17 sites. During the surveying period, the changes of the percentage of water loss were appeared $35.5\;{\sim}\;53.8%$. COD and $H_2S$ were showed $3.8\l{\sim}\;12.9\;mg/g$, and $0.1\;{\sim}11.4\;{\mu}g/g$, respectively, In composition of grain size on the sediment, percentages of grain sizes under $74\;{\mu}m$ were varied from 40.5% to 86.7% and above $74\;{\mu}m$ were varied from 11.5% to 43.0%. From the spatial distribution of heavy metal using contour map, we can suppose some heavy metal discharges which affect sediment of Kwangyang Bay, It was estimated that Shinpung creek, Ssang-bong creek, and draining area of sewange treatment plant were the main discharge among the heavy metal output sources. By comparison between present study and heavy metal guideline of nonpolluted sea sediment that is provided by EPA, US, it was showed that the contents of Pb and Hg were acceptable but contents of Mn, Zn, Cu, Fe, As, and Cr were higher than those of EPA guideline.

• Journal of Korea Port Economic Association
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• v.26 no.1
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• pp.43-60
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• 2010

The purpose of this paper is to show the clustering measurement way for Korean container terminals by using neural network based SOM(Self Organizing Map). Inputs[Number of Employee, Quay Length, Container Terminal Area, Number of Gantry Crane], and output[TEU] are used for 3 years(2002,2003, and 2004) for 8 Korean container terminals by applying both DEA and SOM models. Empirical main results are as follows: First, the result of DEA analysis shows the possibility for clustering among the terminals and reference terminals except Gamcheon and Gwangyang terminals because of the locational closeness. Second, the result of neural network based SOM clustering analysis shows the positive clustering in clustering positions 1, 2, 3, 4, and 5. Third, the results between SOM clustering and DEA clustering show the matching ratio about 67%. The main policy implication based on the findings of this study is that the port policy planner of Ministry of Land, Transport and Maritime Affairs in Korea should introduce the clustering measurement way for the Korean container terminals using neural network based SOM with DEA models for clustering Korean ports and terminals.

• Journal of the Korea Society of Computer and Information
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• v.20 no.6
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• pp.141-150
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• 2015

The aim of this study is to analysis the efficiency of the Long-term Care facilities as well as make counterproposals to conduct of efficient management for the Long-term Care facilities. The data of professionals states of Long-term Care facilities and wages state of Long-term Care facilities from regions in 2014. To analyse the data, the number of professionals and facilities are an input variable whereas the size of number and wages are the output variables. The results showed as below. First, according to the CCR test, Kangwon, Gyeonggi, GyeongNam, Deajeon, Seoul, Ulsan, Incheon, Jeju, and Chong Buk showed significance, but Daegu and Busan showed no significance. Second, the BCC result showed that Kangwon, Gyeonggi, GyeongNam, Deajeon, Seoul, Ulsan, Incheon, Jeju, and Chong Buk has efficiency whereas Daegu and Busan has no efficiency. The result of excess efficieincy analysis confirmed 133.5% in Jeju as the highest area, 37.54% of the highest efficiency of the care provider, and 28.61% of imporvable possibility with doctor's number. The realization of increasing numbers, the ensure of the doctor's number, and consolidating of the care provider's the espertise are required for the future.