• Proceedings of the Korea Water Resources Association Conference
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• 2010.05a
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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.

• Proceedings of the Korea Water Resources Association Conference
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• 2010.05a
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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.

• Proceedings of the Korea Water Resources Association Conference
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• 2010.05a
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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.

• Journal of Korean Society of Transportation
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• v.32 no.5
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• pp.522-530
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• 2014

Spatio-temporal congestion evolution pattern can be reproduced using the VDS(Vehicle Detection System) historic speed dataset in the TMC(Traffic Management Center)s. Such dataset provides a pool of spatio-temporally experienced traffic conditions. Traffic flow pattern is known as spatio-temporally recurred, and even non-recurrent congestion caused by incidents has patterns according to the incident conditions. These imply that the information should be useful for traffic prediction and traffic management. Traffic flow predictions are generally performed using black-box approaches such as neural network, genetic algorithm, and etc. Black-box approaches are not designed to provide an explanation of their modeling and reasoning process and not to estimate the benefits and the risks of the implementation of such a solution. TMCs are reluctant to employ the black-box approaches even though there are numerous valuable articles. This research proposes a more readily understandable and intuitively appealing data-driven approach and developes an algorithm for identifying congestion patterns for recurrent and non-recurrent congestion management and information provision.

• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 2002.09a
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• pp.163-170
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• 2002

A new seismic design criteria of electric transmission and substation facilities has been proposed. For this propose, the historic data of the earthquake damage and the state-of-the-art of the facilities were carefully reviewed and evaluated. Based on the results, a most reasonable and efficient design criteria has been extracted and proposed for the practical design of the facilities. The criteria is expected to be effectively used for obtaining the seismic safety of newly constructed or extensioning facilities. However, an independent criteria is required to evaluate and improve the seismic capacity of existing facilities

• Management Science and Financial Engineering
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• v.20 no.1
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• pp.1-9
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• 2014

In multi-objective scheduling problems, the objectives are usually in conflict. To obtain a satisfactory compromise and resolve the issue of NP-hardness, most existing works have suggested employing meta-heuristic methods, such as genetic algorithms. In this research, we propose a novel data-driven approach for generating a single solution that compromises multiple rules pursuing different objectives. The proposed method uses a data mining technique, namely, random forests, in order to extract the logics of several historic schedules and aggregate those. Since it involves learning predictive models, future schedules with the same previous objectives can be easily and quickly obtained by applying new production data into the models. The proposed approach is illustrated with a simulation study, where it appears to successfully produce a new solution showing balanced scheduling performances.

• Proceedings of the Korea Water Resources Association Conference
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• 2007.05a
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• pp.1464-1468
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• 2007

The restoration project of Cheonggyecheon was conducted to creates the refreshing water-friendly environment in the downtown Seoul. It already have passed almost 2 years after restoration. This project changed environment of Cheonggyecheon dramatically, so historic hydrological data became useless. There are not so many hydrological data to manage and control this newly restored urban stream. The main purpose of this study is collecting and analysing the hydrological data of Cheonggyecheon. At first, we analysed the mechanism of Cheonggyecheon discharge using the sewage design maps and some GIS data. We also monitored the water levels and discharges of 5 main points of Cheonggyecheon. Rating curves of these 5 points were derived. There were 249 blocks of water gates which were located at both sides of bank. We also monitored the behaviors of these water gates. Through the these monitorings, some equations were derived to give useful information to the manager of Cheonggyecheon.

• Journal of Korea Water Resources Association
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• v.39 no.5 s.166
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• pp.467-478
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• 2006

Water supply reliability for a dam is defined with a concept of probabilistic reliability. An evaluation procedure of the water supply reliability is shown with an analysis of long term firm yield reliability. The water supply reliabilities of Soyanggang Dam and Chungju Dam were evaluated. To evaluate the water supply reliability, forty one sets of monthly runoff series were generated by SAMS-2000. HEC-5 model was applied to the reservoir simulation to compute the firm yield from a monthly data of time series. The water supply reliability of the firm yield from the design runoff data of Soyanggang Dam is evaluated by 80.5 % for a planning period of 50 years. The water supply reliability of the firm yield from the historic runoff after the dam construction is evaluated by 53.7 %. The firm yield from the design runoff is 1.491 billion $m^3$/yr and the firm yield from the historic runoff is 1.585 billion $m^3$/yr. If the target draft Is 1.585 billion $m^3$/yr, additional water of 0.094 billion $m^3$ could be supplied every year with its risk. From the similar procedures, the firm yield from the design runoff of Chungju Dam is evaluated 3.377 billion $m^3$/yr and the firm yield from the historic runoff is 2.960 billion $m^3$/yr. If the target draft is 3.377 billion $m^3$/yr, water supply insufficiency occurs for all the sets of time series generated. It may result from overestimation of the spring runoff used for design. The procedure shown can be a more objective method to evaluate water supply reliability of a dam.

• Journal of architectural history
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• v.15 no.1 s.45
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• pp.41-60
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• 2006

Preservation of wooden architecture by means of synthetic resin, is physical and chemical work. Synthetic resins are using for consolidation and restoration of decayed members. Since 1978, synthetic resin became useful preservation of architectural heritage in Korea. The first object was Chimgyeru of Songgwang-temple in Suncheon city. In the 1980s, have begun the care of materials for conservation on the architectural heritage, it was influenced according to authenticity of UNESCO Venice charter's principle, in 1964. In Korea, preservation of wooden architecture by means of synthetic resin that is sing many kinds of epoxies. Among the specific types of epoxies are araldite XN1023, SV427, etc. The use of synthetic resin have merits and demerits in the restoration for architectural heritage. The merit is that it is more smaller change with new members during preservation work. But the demerit is an irreversibility of the epoxy resin. In 1999, 'ICOMOS International Wood Committee' recommend contemporary materials and techniques, should be chosen and used with the greatest caution. And preservation work should reversible, as possible as technically. Therefore, should be data continous for preservation of wooden architecture by synthetic resin. Because data is very important work about a preservation of wooden architecture by synthetic resin. And should be try to think about new materials and techniques instead of synthetic resin, in the long view.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1571-1576
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• 2005

DCS has many processing components and various communication elements. And its communication delay characteristic is affected diverse operating situation and context. Especially, binding signal which traversed from one control-node to another control-node undergo all sort of delay conditions. So its delay value has large deviation with the lapse of time, and the measurement of delay statistics during long time is very difficult by using general oscilloscope or other normal instruments. This thesis introduces the design and implementation of PC-based BDAS(Binding Delay Analysis System) System developed to overcomes these hardships. The system has signal-generator, IO-card, data-acquisition module, delay-calculation and analyzer module, those are implemented on industrial standard PC/Ethernet hardware and Windows/Linux platforms. This system can detect accurate whole-system-wide delay time including io, control processing and network delay, in the resolution of msec unit, and can analyze each channel's delay-historic data which is maintained by realtime database. So, this system has strong points of open system architecture, for example, user-friendly environment, low cost, high compatibility, simplicity of maintenance and high extension ability. Of all things, the measuring capability of long-time delay-statistics obtained through historic-DB make the system more valuable and useful, which function is essential to analyze accurate delay performance of DCS system. Using this system, the verification of delay performance of DCS for nuclear power plants is succeeded in KNICS(Korea Nuclear Instrumentation & Control System) projects