• Proceedings of the Korea Inteligent Information System Society Conference
• /
• 1999.03a
• /
• pp.175-186
• /
• 1999

Detecting the features of significant patterns from their own historical data is so much crucial to good performance specially in time-series forecasting. Recently, a new data filtering method (or multi-scale decomposition) such as wavelet analysis is considered more useful for handling the time-series that contain strong quasi-cyclical components than other methods. The reason is that wavelet analysis theoretically makes much better local information according to different time intervals from the filtered data. Wavelets can process information effectively at different scales. This implies inherent support for multiresolution analysis, which correlates with time series that exhibit self-similar behavior across different time scales. The specific local properties of wavelets can for example be particularly useful to describe signals with sharp spiky, discontinuous or fractal structure in financial markets based on chaos theory and also allows the removal of noise-dependent high frequencies, while conserving the signal bearing high frequency terms of the signal. To data, the existing studies related to wavelet analysis are increasingly being applied to many different fields. In this study, we focus on several wavelet thresholding criteria or techniques to support multi-signal decomposition methods for financial time series forecasting and apply to forecast Korean Won / U.S. Dollar currency market as a case study. One of the most important problems that has to be solved with the application of the filtering is the correct choice of the filter types and the filter parameters. If the threshold is too small or too large then the wavelet shrinkage estimator will tend to overfit or underfit the data. It is often selected arbitrarily or by adopting a certain theoretical or statistical criteria. Recently, new and versatile techniques have been introduced related to that problem. Our study is to analyze thresholding or filtering methods based on wavelet analysis that use multi-signal decomposition algorithms within the neural network architectures specially in complex financial markets. Secondly, through the comparison with different filtering techniques results we introduce the present different filtering criteria of wavelet analysis to support the neural network learning optimization and analyze the critical issues related to the optimal filter design problems in wavelet analysis. That is, those issues include finding the optimal filter parameter to extract significant input features for the forecasting model. Finally, from existing theory or experimental viewpoint concerning the criteria of wavelets thresholding parameters we propose the design of the optimal wavelet for representing a given signal useful in forecasting models, specially a well known neural network models.

• Proceedings of the Computational Structural Engineering Institute Conference
• /
• 2009.04a
• /
• pp.534-535
• /
• 2009

This paper deals with BEM analysis of transient elastodynamic problems using domain decomposition method and particular integrals. The particular method is used to approximate the acceleration term in the governing equation. The domain decomposition method is examined to consider multi-region problems. The domain of the original problem is subdivided into sub-regions, which are modeled by the particular integral BEM. The iterative coupling employing Schwarz algorithm is used for the successive update of the interface boundary conditions until convergence is achieved. The numerical results, compared with those by ABAQUS, demonstrate the validity of the present formulation.

• Proceedings of the KSME Conference
• /
• 2001.06c
• /
• pp.170-175
• /
• 2001

The design cycle associated with large engineering systems requires an initial decomposition of the complex system into design processes which are coupled through the transference of output data. Some of these design processes may be grouped into iterative subcycles. In analyzing or optimizing such a coupled system, it is essential to determine the best order of the processes within these subcycles to reduce design cycle time and cost. This is accomplished by decomposing large multidisciplinary problems into several multidisciplinary analysis subsystems (MDASS) and processing it in parallel. This paper proposes new strategy for parallel decomposition of multidisciplinary problems to improve design efficiency by using the multiple objective genetic algorithm (MOGA), and a sample test case is presented to show the effects of optimizing the sequence with MOGA.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2009.04a
• /
• pp.320-325
• /
• 2009

In this study, a method to estimate the suspension bridge deflection is developed using mode decomposition technique. In order to examine the suspension bridge stability against these dynamic loadings, the prediction of displacement response is very important to evaluate bridge stability. However, it is recognized that any measurement of movement for suspension bridges may be difficult for the absence of proper methods to measure the displacement response on site. This study aims at suggesting a method to estimate the displacement response from the measured strain signals in an indirect way to predict the displacement response, not a direct way to measure the displacement response. Additionally, by applying the FBG sensors with multi-point measurements not influenced by electric noise, it can be expected that the technique would be applicable to infrastructures.

• Journal of Mechanical Science and Technology
• /
• v.16 no.5
• /
• pp.609-618
• /
• 2002

In practical designs, most of the multidisciplinary problems have a large-size and complicate design system. Since multidisciplinary problems have hundreds of analyses and thousands of variables, the grouping of analyses and the order of the analyses in the group affect the speed of the total design cycle. Therefore, it is very important to reorder and regroup the original design processes in order to minimize the total computational cost by decomposing large multidisciplinary problems into several multidisciplinary analysis subsystems (MDASS) and by processing them in parallel. In this study, a new decomposition method is proposed for parallel processing of multidisciplinary design optimization, such as collaborative optimization (CO) and individual discipline feasible (IDF) method. Numerical results for two example problems are presented to show the feasibility of the proposed method.

• Industrial Engineering and Management Systems
• /
• v.1 no.1
• /
• pp.73-78
• /
• 2002

In this paper, we propose a constrained optimization model for conjoint analysis (a preference decomposition technique) to improve parameter estimation by restricting the relative importance of the attributes to an extent as decided by the respondents. Quite simply, respondents are asked to provide some pairwise attribute comparisons that are then incorporated as additional constraints in a linear programming model that estimates the partial preference values. This data collection method is typical in the analytic hierarchy process. Results of a simulation study show the new model can improve the predictive accuracy in partial value estimation by ordinal east squares (OLS) regression.

• Wind and Structures
• /
• v.21 no.4
• /
• pp.425-442
• /
• 2015

This paper discusses the processing of the wind loads measured in wind tunnel tests by means of multi-channel pressure scanners, in order to compute the response of 3D structures to atmospheric turbulence in the time domain. Data compression and the resulting computational savings are still a challenge in industrial contexts due to the multiple trial configurations during the construction stages. The advantage and robustness of the bi-orthogonal decomposition (BOD) is demonstrated through an example, a sail glass of the Fondation Louis Vuitton, independently from any tentative physical interpretation of the spatio-temporal decomposition terms. We show however that the energy criterion for the BOD has to be more rigorous than commonly admitted. We find a level of 99.95 % to be necessary in order to recover the extreme values of the loads. Moreover, frequency limitations of wind tunnel experiments are sometimes encountered in passing from the scaled model to the full scale structure. These can be alleviated using a spectral extension of the temporal function terms of the BOD.

• Proceedings of the Computational Structural Engineering Institute Conference
• /
• 2000.04b
• /
• pp.177-186
• /
• 2000

An improved multi-level（IML) optimization algorithm using automatic differentiation (AD) for multi-objective optimum design of framed structures is proposed in this paper. In order to optimize the steel frames under seismic load, two main objective functions need to be considered for minimizing the structural weight and maximizing the strain energy. For the efficiency of the proposed algorithm, multi-level optimization techniques using decomposition method that separately utilizes both system-level and element-level optimizations and an artificial constraint deletion technique are incorporated in the algorithm. And also to save the numerical efforts, an efficient reanalysis technique through approximated structural responses such as moments, frequencies, and strain energy with respect to intermediate variables is proposed in the paper. Sensitivity analysis of dynamic structural response is executed by AD that is a powerful technique for computing complex or implicit derivatives accurately and efficiently with minimal human effort. The efficiency and robustness of the IML algorithm, compared with a plain multi-level (PML) algorithm, is successfully demonstrated in the numerical examples.

• Proceedings of the Korean Society of Propulsion Engineers Conference
• /
• 2017.05a
• /
• pp.117-119
• /
• 2017

The multi-stage catalytic igniter for hybrid rocket auto ignition is described in this paper. After charging the catalyst and pre-heating the first stage, the $N_2O$ was supplied at the first stage with the low mass flow rate, and then the $N_2O$ with the high flow rate was supplied into the second stage. Even though the $N_2O$ flow rate was high, it was decomposed by supplying the high temperature gas which was evolved from the $N_2O$ decomposition in the first stage. This multi-stage ignitor resulted in the decrease of the ignition time in comparison with the previous ignitor, and confirmed the possibility of $N_2O$ decomposition with the high flow rate using the multi-stage catalytic-ignition system.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.40 no.12
• /
• pp.2331-2342
• /
• 2015

In this paper, we design non-linear transmitter and receiver using a uniform channel decomposition (UCD) to take account of inter-cell interference in multi-cell downlink systems. The designed UCD scheme brings forth the same SINR for all sub-channels in each cell. It provides great convenience to modulation/coding process and achieves the maximum diversity gain. The simulation results confirm that it exhibits a lower BER than the conventional method.