• Korean Journal of Remote Sensing
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• v.25 no.6
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• pp.465-474
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• 2009

Convective/stratiform radar echo classification schemes by Steiner et al. (1995) and Biggerstaff and Listemaa (2000) are examined on a monsoonal front during the summer monsoon-Changma period, which is organized as a cloud cluster with mesoscale convective complex. Target radar is S-band with wavelength of 10cm, spatial resolution of 1km, elevation angle interval of 0.5-1.0 degree, and minimum elevation angle of 0.19 degree at Jindo over the Korean Peninsula. For verification of rainfall amount retrieved from the echo classification, ground-based rain gauge observations (Automatic Weather Stations) are examined, converting the radar echo grid data to the station values using the inverse distance weighted method. Improvement from the echo classification is evaluated based on the correlation coefficient and the scattered diagram. Additionally, an optimal use method was designed to produce combined rainfalls from the radar echo and Tropical Rainfall Measuring Mission Precipitation Radar (TRMM/PR) data. Optimal values for the radar rain and TRMM/PR rain are inversely weighted according to the error variance statistics for each single station. It is noted how the rainfall distribution during the summer monsoon frontal system is improved from the classification of convective/stratiform echo and the use of the optimal use technique.

• Journal of The Korean Society of Agricultural Engineers
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• v.50 no.3
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• pp.91-104
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• 2008

This study developed the WSM (weighted scenario method)-AHP method that can optimize the weighting value for multi-criteria to make GIS grid-based potential surface. The potential surface has been used to simulate urban expansion using distributed cellular automata model and to generate land-use planning as basic data. This study formulated the WSM-AHP method in mathematically and applied to test region, Suwon city, which located on south area from Seoul. WSM-AHP method generates potential map for each pair of weighting value for all criteria, which one criterion is weighted with high weighting value and the others use low weighting value, considering that the summation for all criteria weighting values should be "1". The potential change rate to the step of weighted scenario for weighting value of criteria is standardized like AHP intensity matrix in this study. From the standard potential change rate, WSM-AHP intensity matrix is completed, and then the optimal weighting value is calculated from the maximum eigenvector of the WSM-AHP matrix, according to the new WSM-AHP method developed in this study. The applied results of new method showed that the optimal weighting value from WSM-AHP is more resonable than the general AHP specialists' evaluation for weighting value. The another new finding of this study is to suggest the deterministic approach to optimize the weighting value for the distributed CA model, which is used to find new city area and to generate rational land-use planning.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.16 no.2
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• pp.111-120
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• 2004

The optimal design method of indoor thermal environment using CFD coupled simulation and genetic algorithms (GA) is developed in this study. CFD could analyze the thermal environment considering the distribution of temperature, velocity, etc. in a room. Therefore, It would be appropriate to use CFD for the optimal design method considering their distribution. In this paper, the optimal design means the most appropriate boundary conditions of the room among the conditions where the design target of indoor therm environment is achieved. Two step optimal indoor thermal environment design method is proposed. It includes the GA for searching the optimal indoor thermal environment design. To examine the performance of this method, the optimal design of hybrid ventilation system, which uses the natural cross ventilation and the radiation-cooling panel is conducted. The optimal design which satisfies the design target (thermal comfort, minimum cooling load, minimum vertical temperature difference) is found using two step optimal design method.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1171-1173
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• 2003

There are two datasets to estimate the area-mean and time-mean precipitation rate. For one, an array of surface rain gauges represents a series of rods that have to the time axis of the volume. And another data is that of a remote sensing make periodic overpasses at a fixed interval such as radar. The problem of optimally combining data from surface rain gauge data and remote sensed data is considered. In order to combining remote sensed data with Automatic Weather Station (AWS), we use optimal weighting method, which is similar to the method of [2]. They had suggested optimal weights that minimized value of the mean square error. In this paper, optimal weight is evaluated for the cases such as Changma, summer Monsoon, Typhoon and orographic rain.

• Journal of the Korean Mathematical Society
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• v.49 no.1
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• pp.99-112
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• 2012

This paper attempts to present a numerical method for solving optimal control problems. The method is based upon constructing the n-th degree Jacobi polynomials to approximate the control vector and use differentiation matrix to approximate derivative term in the state system. The system dynamics are then converted into system of algebraic equations and hence the optimal control problem is reduced to constrained optimization problem. Numerical examples illustrate the robustness, accuracy and efficiency of the proposed method.

• Journal of applied mathematics & informatics
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• v.13 no.1_2
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• pp.183-194
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• 2003

We will explain a new method for obtaining the nearly optimal domain for optimal shape design problems associated with the solution of a nonlinear wave equation. Taking into account the boundary and terminal conditions of the system, a new approach is applied to determine the optimal domain and its related optimal control function with respect to the integral performance criteria, by use of positive Radon measures. The approach, say shape-measure, consists of two steps; first for a fixed domain, the optimal control will be identified by the use of measures. This function and the optimal value of the objective function depend on the geometrical variables of the domain. In the second step, based on the results of the previous one and by applying some convenient optimization techniques, the optimal domain and its related optimal control function will be identified at the same time. The existence of the optimal solution is considered and a numerical example is also given.

• Journal of Korean Society of Rural Planning
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• v.14 no.2
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• pp.55-64
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• 2008

This study aims to analyze the sensitivity of WSM(weighted scenario method)-AHP method according to variation of nonlinear exponent for accessibility criteria, which are used to make urbanization potential maps with the optimal weighting value for multiple criteria in grid-based GIS technique. Besides this study tried to develop WSM-AHP2 which is simplified by using rank of the potential value for each scenario. The two methods were applied to the test area, Suwon city located south area of Seoul, with time series land-use maps of 1986 and 1996. The evaluation system of urbanization potential have 7 criteria including 6 accessibility criteria. The results of WSM-AHP2, the optimal weighting values and their corresponding potential maps, have almost similar with those of WSM-AHP. In the application of CA(cellular automata) model for expansion of urbanized area using the three potential maps by WSM-AHP, WSM-AHP2, and specialists's AHP evaluation, it also showed that the accuracy of simulation for actual urban area is the highest in the potential map of WSM-AHP, followed by WSM-AHP2 and specialists's AHP evaluation. From the results of this study, WSM-AHP and simplified WSM-AHP2 will be used to generate the optimal potential maps for land-use planning in urban fringe area.

• Proceedings of the KSR Conference
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• 1998.05a
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• pp.442-449
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• 1998

Since it is essential for traction motors to reduce size and weight to achieve given traction effort, they need high input voltage. But the lack of input voltage occurs periodically due to the characteristics of train system. Therefore traction inverters use over-modulation PWM to maximize inverter's voltage gain. On the other hand, IGBT inverters can use higher frequency twice than GTO ones, which resulted in the need for novel optimal synchronous PWM strategy. This paper suggests that linearly-compensated overmodulation/optimal synchronous PWM strategy and also the simulation results of the method for a real traction motor-intertia model are presented.

• Proceedings of the KIEE Conference
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• 1999.07g
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• pp.2911-2913
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• 1999

This paper suggest an optimal identification method to complex and nonlinear system modeling that is based on Fuzzy-Neural Network(FNN). The FNN modeling implements parameter identification using HCM algorithm and optimal identification algorithm structure combined with two types of optimization theories for nonlinear systems, we use a HCM Clustering Algorithm to find initial parameters of membership function. The parameters such as parameters of membership functions, learning rates and momentum coefficients are adjusted using optimal identification algorithm. The proposed optimal identification algorithm is carried out using both a genetic algorithm and the improved complex method. Also, an aggregate objective function(performance index) with weighted value is proposed to achieve a sound balance between approximation and generalization abilities of the model. To evaluate the performance of the proposed model, we use the time series data for gas furnace, the data of sewage treatment process and traffic route choice process.

• Journal of the Korea Society of Computer and Information
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• v.24 no.1
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• pp.137-143
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• 2019

As the performance of computers increases, the use of deep learning, which has faced technical limitations in the past, is becoming more diverse. In many fields, deep learning has contributed to the creation of added value and used on the bases of more data as the application become more divers. The process for obtaining a better performance model will require a longer time than before, and therefore it will be necessary to find an optimal model that shows the best performance more quickly. In the artificial neural network modeling a tuning process that changes various elements of the neural network model is used to improve the model performance. Except Gride Search and Manual Search, which are widely used as tuning methods, most methodologies have been developed focusing on heuristic algorithms. The heuristic algorithm can get the results in a short time, but the results are likely to be the local optimal solution. Obtaining a global optimal solution eliminates the possibility of a local optimal solution. Although the Brute Force Method is commonly used to find the global optimal solution, it is not applicable because of an infinite number of hyper parameter combinations. In this paper, we use a statistical technique to reduce the number of possible cases, so that we can find the global optimal solution.