• Korean Journal of Computational Design and Engineering
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• v.3 no.1
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• pp.57-67
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• 1998

Genetic programming (GP) is an extension of a genetic algoriths paradigm, deals with tree structures representing computer programs as individuals. In recent, there have been many research activities on applications of GP to various engineering problems including system identification, data mining, function approximation, and so forth. However, standard GP suffers from the lack of the estimation techniques for numerical parameters of the GP tree that is an essential element in treating various engineering applications involving real-valued function approximations. Unlike the other research activities, where nonlinear optimization methods are employed, I adopt the use of a weighted linear associative memory for estimation of these parameters under GP algorithm. This approach can significantly reduce computational cost while the reasonable accurate value for parameters can be obtained. Due to the fact that the GP algorithm is likely to fall into a local minimum, the GP algorithm often fails to generate the tree with the desired accuracy. This motivates to devise a group of additive genetic programming trees (GAGPT) which consists of a primary tree and a set of auxiliary trees. The output of the GAGPT is the summation of outputs of the primary tree and all auxiliary trees. The addition of auxiliary trees makes it possible to improve both the teaming and generalization capability of the GAGPT, since the auxiliary tree evolves toward refining the quality of the GAGPT by optimizing its fitness function. The effectiveness of this approach is verified by applying the GAGPT to the estimation of the principal dimensions of bulk cargo ships and engine torque of the passenger car.

• Journal of the Korean Geotechnical Society
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• v.30 no.11
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• pp.39-49
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• 2014

Volcanic rocks in Jeju island show vesicular structure caused by various environmental factors, and indicate the differences in geological and mechanical characteristics from region to region. Previous studies on the volcanic rocks in Jeju island have been actively conducted on geological and chemical properties in terms of geophysics and geology and on physical and mechanical properties in terms of engineering. But comprehensive comparative analysis on physical and mechanical properties of volcanic rocks in Jeju island is not conducted. In this study, the physical and mechanical properties of volcanic rocks in Jeju island were compared and analyzed comprehensively through the existing research papers and reports about volcanic rocks in Jeju island. As a result, it was found that the relationship between absorption (porosity) and apparent specific gravity is commonly linear and could be represented as two different linear approximations. In addition, it was found that the relationship between P-wave velocity and S-wave velocity and the relationship between absorption (porosity) and uniaxial compressive strength could be classified more clearly, considering two different linear relationships in absorption (porosity) and apparent specific gravity.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.147-147
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• 2019

The Numerical Weather Prediction (NWP) models determine the future state of the weather by forcing current weather conditions into the atmospheric models. The NWP models approximate mathematically the physical dynamics by nonlinear differential equations; however these approximations include uncertainties. The errors of the NWP estimations can be related to the initial and boundary conditions and model parameterization. Development in the meteorological forecast models did not solve the issues related to the inevitable biases. In spite of the efforts to incorporate all sources of uncertainty into the forecast, and regardless of the methodologies applied to generate the forecast ensembles, they are still subject to errors and systematic biases. The statistical post-processing increases the accuracy of the forecast data by decreasing the errors. Error prediction of the NWP models which is updating the NWP model outputs or model output statistics is one of the ways to improve the model forecast. The regression methods (including linear, polynomial and scaling regression) are applied to the present study to improve the real time forecast skill. Such post-processing consists of two main steps. Firstly, regression is built between forecast and measurement, available during a certain training period, and secondly, the regression is applied to new forecasts. In this study, the WRF real-time forecast data, in comparison with the observed data, had systematic biases; the errors related to the NWP model forecasts were reflected in the underestimation of the meteorological data forecast by the WRF model. The promising results will indicate that the post-processing techniques applied in this study improved the meteorological forecast data provided by WRF model. A comparison between various bias correction methods will show the strength and weakness of the each methods.

• Journal of the Korea Institute of Military Science and Technology
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• v.26 no.1
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• pp.10-21
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• 2023

For various target tracking applications, it is well known that the Kalman filter is the optimal estimator(in the minimum mean-square sense) to predict and estimate the state(position and/or velocity) of linear dynamical systems driven by Gaussian stochastic noise. In the case of nonlinear systems, Extended Kalman filter(EKF) and/or Unscented Kalman filter(UKF) are widely used, which can be viewed as approximations of the(linear) Kalman filter in the sense of the conditional expectation. However, to implement EKF and UKF, the exact dynamical model information and the statistical information of noise are still required. In this paper, we propose the recurrent neural-network based Kalman filter, where its Kalman gain is obtained via the proposed GRU-LSTM based neural-network framework that does not need the precise model information as well as the noise covariance information. By the proposed neural-network based Kalman filter, the state estimation performance is enhanced in terms of the tracking error, which is verified through various linear and nonlinear tracking problems with incomplete model and statistical covariance information.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.13 no.1
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• pp.47-57
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• 2003

In this paper, we firstly evaluate the resistance of the reduced 5-round version of the block cipher CIKS-1 against linear cryptanalysis(LC) and show that we can attack full-round CIKS-1 with \ulcorner56-bit key through the canonical extension of our attack. A feature of the CIKS-1 is the use of both Data-Dependent permutations(DDP) and internal key scheduling which consist in data dependent transformation of the round subkeys. Taking into accout the structure of CIKS-1 we investigate linear approximation. That is, we consider 16 linear approximations with p=3/4 for 16 parallel modulo $2^2$ additions to construct one-round linear approximation and derive one-round linear approximation with the probability P=1/2+$2^{-17}$ by Piling-up lemma. Then we present 3-round linear approximation with 1/2+$2^{-17}$ using this one-round approximation and attack the reduced 5-round CIKS-1 with 64-bit block by LC. In conclusion we present that our attack requires $2^{38}$chosen plaintexts with a probability of success of 99.9% and about $2^{67-7}$encryption times to recover the last round key.(But, for the full-round CIKS-1, our attack requires about $2^{166}$encryption times)

• Journal of the Korea Institute of Information Security & Cryptology
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• v.12 no.6
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• pp.59-69
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• 2002

Many Linear attacks have introduced after M. Matsui suggested Linear Cryptanalysis in 1993. The one of them is the method suggested by B. Kaliski and M. Robshaw. It was a new method using multiple linear approximations to attack for block ciphers. It requires less known plaintexts than that of Linear Cryptanalysis(LC) by Matsui, but it has a problem. In this paper, we will introduce the new method using multiple linear approximation that can solve the problem. Using the new method, the requirements of the known plaintexts is 5(1.25) times as small as the requirements in LC on 8(16) round DES with a success rate of 95%(86%) respectively. We can also adopt A Chosen Plaintext Linear Attack suggested by L. R. Knudsen and J. E. Mathiassen and then our attack requires about $2^{40.6}$ chosen plaintexts to recover 15 key bits with 86% success rate. We believe that the results in this paper contain the fastest attack on the DES full round reported so far in the open literature.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.12 no.3
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• pp.397-406
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• 1999

A new solution procedure for approximate reanalysis, using the staged hybrid methods with substructuring, is proposed in this study. Displacements are calculated with two step mixed procedures. First step is to introduce the conservative approximation, which is a hybrid form of the linear and reciprocal approximation, as local approximation. In the next step, it is combined with the global approximation by reduced basis approach. Stresses are evaluated from the displacements by matrix transformation. The quality of reanalyzed quantities can be greatly improved through these staged hybrid approximations, specially for large changes in the design. Overall procedures are based on substructuring scheme. Several numerical examples illustrate the validity and effectiveness of the proposed methods.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.6 no.1
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• pp.12-22
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• 1994

Time evolution of linear water waves on a constant depth generated by a disturbance is analyzed by asymptotic methods; stationary phase, steepest descents and leading wave approximation. In order to verify the derived formulae of surface displacements for 1-D and 2-D waves. surface displacements are calculated and plotted from both the formulae and a numerical integration. The existing results for surface displacements are verified in which the leading amplitude of 1-D waves during the evolution decays as f- T/B, the rest of the wavetrain as t$^{-1}$ 2/ and the rest of the wavetrain of 2-D waves as t-1. But it is shown that the leading amplitude of 2-D waves decays as t 5/6 which is different from Kajiura's result t$^{-4}$ 3/.

• The KSFM Journal of Fluid Machinery
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• v.7 no.3 s.24
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• pp.32-38
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• 2004

Shape of a multi-blades centrifugal fan is optimized by response surface method based on three-dimensional Navier-Stokes analysis. For numerical analysis, Reynolds-averaged Navier-Stokes equations with standard $k-{epsilon}$ turbulence model are transformed into non-orthogonal curvilinear coordinate system, and are discretized with finite volume approximations. Due to the large number of blades in this centrifugal fan, the flow inside of the fan is regarded as steady flow by introducing the impeller force models for economic calculations. Optimizations with and without constraints are carried out. Design variables, location of cur off, radius of cut off, expansion angle of scroll and width of impeller were selected to optimize the shapes of scroll and blades. Data points for response evaluations were selected by D-optimal design, and linear programming method was used for the optimization on the response surface. As a main result of the optimization, the efficiency was successfully improved. The correlation of efficiency with relative size of inactive zone at the exit of impeller is discussed as well as with average momentum fluxes in the scroll.

• The KIPS Transactions:PartB
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• v.9B no.3
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• pp.271-276
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• 2002

The test statistic in ANOVA tests has a single or doubly noncentral F distribution and the noncentral F distribution is applied to the calculation of the power functions of tests of general linear hypotheses. Although various approximations of noncentral F distribution are suggested, they are troublesome to compute. In this paper, the calculation of noncentral F distribution is applied to the neural network theory, to solve the computation problem. The neural network consists of the multi-layer perceptron structure and learning process has the algorithm of the backpropagation. Using fables and figs, comparisons are made between the results obtained by neural network theory and the Patnaik's values. Regarding of accuracy and calculation, the results by neural network are efficient than the Patnaik's values.