• Journal of Convergence for Information Technology
• /
• v.11 no.1
• /
• pp.109-117
• /
• 2021

In this paper, the meta-model based approximate optimization was carried out for the structure design of an ocean automatic salt collector in order to minimize the structure weight. The structural analysis was performed by using the finite element method to evaluate the strength performance of the ocean automatic salt collector in its initial design. In the structural analysis, it was evaluated the strength performance of the design load conditions. The optimum design problem was formulated so that design variables of main structure thickness would be determined by minimizing the structure weight subject to strength performance constraints. The meta-models used in the approximate optimization were the response surface method, Kriging model, and Chebyshev orthogonal polynomials. Regarding to the numerical characteristics, the solution results from approximate optimization techniques were compared to the results of non-approximate optimization. The Chebyshev orthogonal polynomials among the meta-models used in the approximate optimization showed the most appropriate optimum design results for the structure design of the ocean automatic salt collector.

• East Asian mathematical journal
• /
• v.15 no.1
• /
• pp.135-146
• /
• 1999

• East Asian mathematical journal
• /
• v.14 no.2
• /
• pp.227-235
• /
• 1998

• Proceedings of the Korean Society of Computational and Applied Mathematics Conference
• /
• 2003.09a
• /
• pp.15-15
• /
• 2003

We provide some recent results of approximation algorithms for solving Markov Games and discuss their applications to problems that arise in Computer Science. We consider a receding horizon approach as an approximate solution to two-person zero-sum Markov games with an infinite horizon discounted cost criterion. We present error bounds from the optimal equilibrium value of the game when both players take “correlated” receding horizon policies that are based on exact or approximate solutions of receding finite horizon subgames. Motivated by the worst-case optimal control of queueing systems by Altman, we then analyze error bounds when the minimizer plays the (approximate) receding horizon control and the maximizer plays the worst case policy. We give two heuristic examples of the approximate receding horizon control. We extend “parallel rollout” and “hindsight optimization” into the Markov game setting within the framework of the approximate receding horizon approach and analyze their performances. From the parallel rollout approach, the minimizing player seeks to combine dynamically multiple heuristic policies in a set to improve the performances of all of the heuristic policies simultaneously under the guess that the maximizing player has chosen a fixed worst-case policy. Given $\varepsilon$>0, we give the value of the receding horizon which guarantees that the parallel rollout policy with the horizon played by the minimizer “dominates” any heuristic policy in the set by $\varepsilon$, From the hindsight optimization approach, the minimizing player makes a decision based on his expected optimal hindsight performance over a finite horizon. We finally discuss practical implementations of the receding horizon approaches via simulation and applications.

• International Journal of Aeronautical and Space Sciences
• /
• v.3 no.2
• /
• pp.46-58
• /
• 2002

An inverse method is introduced to construct benchmark problems for the numerical solution of initial value problems. Benchmark problems constructed through this method have a known exact solution, even though analytical solutions are generally not obtainable. The solution is constructed such that it lies near a given approximate numerical solution, and therefore the special case solution can be generated in a versatile and physically meaningful fashion and can serve as a benchmark problem to validate approximate solution methods. A smooth interpolation of the approximate solution is forced to exactly satisfy the differential equation by analytically deriving a small forcing function to absorb all of the errors in the interpolated approximate solution. A multi-variable orthogonal function expansion method and computer symbol manipulation are successfully used for this process. Using this special case exact solution, it is possible to directly investigate the relationship between global errors of a candidate numerical solution process and the associated tuning parameters for a given code and a given problem. Under the assumption that the original differential equation is well-posed with respect to the small perturbations, we thereby obtain valuable information about the optimal choice of the tuning parameters and the achievable accuracy of the numerical solution. Illustrative examples show the utility of this method not only for the ordinary differential equations (ODEs) but for the partial differential equations (PDEs).

• Journal of Biosystems Engineering
• /
• v.20 no.3
• /
• pp.205-216
• /
• 1995

A fast and inexpensive approximate analysis method to predict power output characteristics of the Stilting engines in a preliminary design stage was investigated. In basic equations proposed by Walker, typical temperatures of working fluids in expansion and compression spaces were treated as those of working fluids in heater and cooler respectively. While the temperature of working fluid in the expansion space was actually lower than that of working fluid in the heater, the temperature of working fluid in the compression space was higher than that of working fluids in the cooler. In this paper, the working fluid temperature of expansion space was treated as lower than the heater temperature and that of compression space was treated as higher than the cooler temperature. Also, according to them, the power output characteristics of the Stirling engine were evaluated with respect to the GPU-3 and 4-215 Stilting engines. The following conclusions were drawn from the analysis. 1. Using the available experimental data from the GPU-3 Stirling engine, it was shown that the approximate analysis predicts the brake power with a maximum error of 19 percent at 1, 000rpm and with a minimum error of 3 percent at 2, 000rpm. 2. The approximate analysis data which for the GPU-3 Stirling engine were much closer to the experimental data than those of adiabatic 2nd order and 3rd order analysis within 1, 500rpm to 2, 500rpm. 3. The approximate analysis data which for the GPU-3 and 4-215 Stilting engines were much closer to the experimental data than those of the Beal number analysis.

• Journal of KIISE:Databases
• /
• v.27 no.2
• /
• pp.199-208
• /
• 2000

The k-nearest neighbor search query based on similarity is very important for content-based multimedia information retrieval(MIR). The conventional exact k-nearest neighbor search algorithm is not efficient for the MIR application because multimedia data should be represented as high dimensional feature vectors. Thus, an approximate k-nearest neighbor search algorithm is required for the MIR applications because the performance increase may outweigh the drawback of receiving approximate results. For this, we propose a new approximate k-nearest neighbor search algorithm for high dimensional data. In addition, the comparison of the conventional algorithm with our approximate k-nearest neighbor search algorithm is performed in terms of retrieval performance. Results show that our algorithm is more efficient than the conventional ones.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.8 no.4
• /
• pp.33-39
• /
• 1988

The objective of this paper is to adjust precise traverse nets by matrix analysis. As the result of this paper, In positioning by Traverse nets adjustment, the application of matrix analysis improved the accuracy. And also, the difference between adjustment values of rigorous-method and those of approximate-method appears to be within the mean square errors(0.4 mm~0.9 mm), therefore, the efficiency of approximate-method was proved.

• Transactions of the Korean Society of Mechanical Engineers B
• /
• v.20 no.11
• /
• pp.3620-3629
• /
• 1996

In the free molecular flow range, the pumping performance of a turbomolecular pump has been predicted by calculation of the transmission probability which employs the integral method and the test particle Monte-Carlo method. Also, new approximate method combining the double stage solutions, so called double-approximation, is presented here. The calculated values of transmission probability for the single stage agree quantitatively with the previous known numerical results. For a six-stage pump, the Monte-Carlo method is employed to calculate the overall transmission probability for the entire set of blade rows. When the results of the approximate method combining the single stage solutions are compared with those of the Monte-Carlo method at dimensionless blade velocity ratio C=0.4, the previous known approximate method overestimates as much as 34% than does the Monte-Carlo method. But, the new approximate method gives more accurate results, whose relative error is 10% compared to the Monte-Carlo method, than does the previous approximate method.

• Journal of KIISE:Computing Practices and Letters
• /
• v.16 no.6
• /
• pp.742-746
• /
• 2010

In this paper, we propose new randomness testing methods based on approximate periods in order to improve the previous randomness testing method using exact pattern matching. Finding approximate periods of random sequences enables us to search similarly repeated parts, but it has disadvantages since it takes long time. In this paper we propose randomness testing methods whose time complexity is O($n^2$) by reducing the time complexity of computing approximate periods from O($n^3$) to O($n^2$). Moreover, we perform some experiments to compare pseudo random number generated by AES cryptographic algorithms and true random number.