• Journal of the Korean earth science society
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• v.31 no.5
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• pp.437-447
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• 2010

Spatial estimation of environmental variables has been regarded as an important preliminary procedure for decision-making. A minimum variance criterion, which has often been adopted in traditional kriging algorithms, does not always guarantee the optimal estimates for subsequent decision-making processes. In this paper, a geostatistical framework is illustrated that consists of uncertainty modeling via stochastic simulation and risk modeling based on loss functions for the selection of optimal estimates. Loss functions that quantify the impact of choosing any estimate different from the unknown true value are linked to geostatistical simulation. A hybrid loss function is especially presented to account for the different impact of over- and underestimation of different land-use types. The loss function-specific estimates that minimize the expected loss are chosen as optimal estimates. The applicability of the geostatistical framework is demonstrated and discussed through a case study of copper mapping.

• Journal of applied mathematics & informatics
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• v.26 no.3_4
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• pp.519-530
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• 2008

This paper studies the multi-domain coupled system of one dimensional Arctic temperature field and establishes identification model about the thermodynamic parameters of sea ice (heat storage capacity, density and conductivity) by the so-called output least-square estimate according to the temperature data acquired by a monitor buoy installed in the Arctic ocean. By the optimal control theory, the existence and dependability of weak solution and the identifiability of identification model have been given. Moreover, necessary optimality condition is proposed. Furthermore, the optimal algorithm for the identification model is constructed. By using the optimal thermodynamic parameters of Arctic sea ice, the numerical simulation is implemented, and the numerical results of temperature distribution of Arctic sea ice are demonstrated.

• Bulletin of the Korean Mathematical Society
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• v.57 no.2
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• pp.311-330
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• 2020

This paper investigates infinite horizon optimal control problems driven by a class of backward stochastic delay differential equations in Hilbert spaces. We first obtain a prior estimate for the solutions of state equations, by which the existence and uniqueness results are proved. Meanwhile, necessary and sufficient conditions for optimal control problems on an infinite horizon are derived by introducing time-advanced stochastic differential equations as adjoint equations. Finally, the theoretical results are applied to a linear-quadratic control problem.

• Nuclear Engineering and Technology
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• v.52 no.3
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• pp.552-559
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• 2020

This paper presents an observer-based chattering free robust optimal control scheme to regulate the total power of a nuclear reactor. The non-linear model of nuclear reactor is linearized around a steady state operating point to obtain a linear model for which an optimal second order integral sliding mode controller is designed. A second order integral sliding mode observer is also designed to estimate the unmeasurable states. In order to avoid the chattering effect, the discontinuous input of both observer and controller are designed using the super-twisting algorithm. The proposed controller is realized by combining an optimal linear tracking controller with a second order integral sliding mode controller to ensure minimum control effort and robustness of the closed-loop system in the presence of uncertainties. The condition for the selection of gains of discontinuous control based on the super-twisting algorithm is derived using a strict Lyapunov function. Performance of the proposed observer based control scheme is demonstrated through non-linear simulation studies.

• Genomics & Informatics
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• v.1 no.1
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• pp.20-24
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• 2003

The analysis of DNA microarry data is one of the most important things for functional genomics research. The matrix representation of microarray data and its successive 'optimal' incisional hyperplanes is a useful platform for developing optimization algorithms to determine the optimal partitioning of pairwise proximity matrix representing completely connected and weighted graph. We developed Deterministic Annealing (DA) approach to determine the successive optimal binary partitioning. DA algorithm demonstrated good performance with the ability to find the 'globally optimal' binary partitions. In addition, the objects that have not been clustered at small non­zero temperature, are considered to be very sensitive to even small randomness, and can be used to estimate the reliability of the clustering.

• Proceedings of the Korean Society For Composite Materials Conference
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• 2003.04a
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• pp.91-94
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• 2003

In this paper, we developed a optimal design system to optimize composite shell structures using genetic algorithm and expert system. The objective of the optimal design was to find designs that minimize weight of the structures and satisfy the design rules specified by the user. Buckling analyses of the composite shell structures were done to estimate buckling loads. Some example problems were selected and optimized with the developed system. And a GUI-based integrated design and optimization program, I-DOTCom was developed and introduced at the end of this paper.

• Journal of Korea Society of Digital Industry and Information Management
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• v.13 no.2
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• pp.27-34
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• 2017

Highly informative admissible heuristics can help to conduct more efficient search for optimal solutions. However, in general, more informative ones of heuristics from planning problems requires lots of computational effort. To address this problem, we propose an Delete Relaxation based Action Costs-based Planning Graph(ACPG) and Action Costs-based Heuristics for solving optimal planning problems more efficiently. The ACPG is an extended one to be applied to can find action costs between subgoal & goal conditions from the Relaxed Planning Graph(RPG) which is a common means to get heuristics for solving the planning problems, Action Costs-based Heuristics utilizing ACPG can find action costs difference between subgoal & goal conditions in an effective way, and then consider them to estimate the goal distance. In this paper, we present the heuristics algorithm to compute Action Costs-based Heuristics, and then explain experimental analysis to investigate the efficiency and the accuracy of the Action Costs-based Heuristics.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.3 no.2 s.5
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• pp.129-140
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• 2004

In this paper, we conduct the research about optimal aggregation interval of travel time data on interrupted traffic flow and verify the reliability of AVI collected data by using car plate matching method in RTMS for systematic collection and analysis of link travel time data on interrupted traffic flow rural arterial. We perform Kolmosorov-Smirnov test on AVT collected sample data and on entire population data, and conclude that the sample data does not represent pure random sampling and hence includes sample collection error. We suggest that additional review is necessary to investigate the effectiveness of AVI collected sample data as link representative data. We also develop statistical model by applying two estimation techniques namely point estimation and interval estimation for calculating optimal aggregation interval. We have implemented our model and determine that point estimate is preferable over interval estimate for exactly selecting and deciding optimal aggregation interval. Our final conclusion is that 5-minute aggregation interval is optimal to estimate travel time in RTMS, as is currently being used our investigation is based on AVI data collected from Yang-ji to Yong-in $42^{nd}$ National road.

• Environmental and Resource Economics Review
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• v.23 no.1
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• pp.21-42
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• 2014

In this study, we are estimating the economic effects of the rising sea level due to the climate change in the Korean Eastern and Southern coastal areas. Using disaggregated regional data, we also estimate the optimal rate of coastal protection. We use FUND (The Climate Framework for Uncertainty, Negotiation and Distribution) in order to obtain estimates of the expected inundation ratios by geographical district. Our estimates suggest that in Busan the ratio of inundated land to total territory will likely constitute 3.19% by 2100, while the number in Gangwon-do province is estimated to be lower at only 0.1%. We estimate the associated economic damage to differ by geographical district with the economically active regions such as e.g. Busan and Ulsan cities, or the Gyeongsang-nam-do province, likely to sustain relatively more damage. In Busan and Ulsan where the coastal line is relatively short and the size of expected economic damage is rather high, we estimate the optimal rate of coastal protection to be at the level of 98% and 92%, respectively. In the Kyeongsang-nam-do area that is also likely to suffer a substantial economic damage due to the inundation, we suggest the optimal ratio of coastal protection to be set at the level of 78%~79%. In contrast, in the Kangwon-do province where the expected economic damage is estimated to be low, the optimal rate of coastal protection is estimated to be around 43%, depending on the scenario.

• International Journal of Highway Engineering
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• v.8 no.3 s.29
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• pp.63-76
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• 2006

For a private toll road project, deciding optimal toll is an important element of economic analysis for the project and a challengeable work. In this study, the optimal toll of a private toll bridge, Geoga Bridge which connects Geoje Island of Gyeongnam Province and Gaduk Island of Busan was estimated using Stated Preference (SP) data. The SP data were collected by interviewing the passenger car drivers travelling on the National Road 14. They are latent users of the bridge. A fuzzy approximate reasoning model to estimate the optimal toll was built using the SP data. For the input variable of the model, the saved travel time and toll level were employed and the diversion rate to the bridge was employed for the output variable. The diversion rates for each toll level and saved travel time were estimated and the toll level which had maximized the toll revenue was decided as optimal toll. The optimal toll was tested by comparing with the average pay rate of passenger car drivers. Since the optimal toll for passenger cars at one hour saving, the 6,250 won is about 50 % of the average pay rate of passenger car divers, the toll was evaluated not to be high. The technique employed in this study may be used for the estimation of the optimal tolls for other kinds of vehicles.