• Journal of the Korean Data and Information Science Society
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• 제15권4호
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• pp.803-816
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• 2004

The decision tree approach is most useful in classification problems and to divide the search space into rectangular regions. Decision tree algorithms are used extensively for data mining in many domains such as retail target marketing, fraud dection, data reduction and variable screening, category merging, etc. CHAID uses the chi-squired statistic to determine splitting and is an exploratory method used to study the relationship between a dependent variable and a series of predictor variables. In this paper we propose CHAID algorithm by cube-based proportional sampling and explore CHAID algorithm in view of accuracy and speed by the number of variables.

• 대한산업공학회지
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• 제23권2호
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• pp.289-305
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• 1997

In this paper, design procedure and estimation of the double sampling plans are developed when the production process is examined in order and if it shows the dependence between the products. If a dependent process model can be simulated, the best sampling plans can be selected by using the special properties of the probability structure. The number of actual evaluations to find the plans can be reduced remarkably. The experimental study reveals that only small portion of the total exhaustive enumeration is needed. ARMA (1,1) time series models are given as numerical examples.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1996년도 추계학술대회 논문집 학회본부
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• pp.49-51
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• 1996

The z-transform method is a basic mathematical tool in analyzing and designing sampled-data control systems. However, since the z-transform method relates only the sampling-instants signals, another mathematical tool is necessary to describe the continous signals between the sampling instants. For this purpose the delayed and the modi fled z-transform methods were developed. The definition of the modi fled z-transform includes a sample in the interval [-T,0] of the original signal in its series expression, where the signal value is always zero for any physical system. From this reason one step skew of the time index always appears in its application formulas. This introduces an unnecessary operation and a gap in linking the mathematical formula and its physical interpretation. Considering the conceptual difficulty and application inconvenience, a method of using the advanced z-transform in analysis of sampled-data control systems is developed as a replacement of the modi fled z-transform. With one formulation of the advanced z-transform, now it is possible to relate both the signals of the sampling instants and those in between without any complication and conceptual difficulty.

• Journal of Information Processing Systems
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• 제19권2호
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• pp.164-172
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• 2023

Through theoretical proof and algorithm design, this paper numerically demonstrates that the three sampling methods of DDS are equivalent in amplitude-frequency characteristics. Depending on theoretical analysis, the article obtains the conclusion that 2 points are optimal when sampling at 2, 3, and 4 points. Built on the data results, this paper obtains the fractional form of the amplitude and phase of the DDS sampled signal; in addition, this paper also obtains the design parameters of the DDS post-stage filter. It also gives a control method for the calculation error when addressing this issue.

• Structural Engineering and Mechanics
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• 제84권3호
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• pp.323-335
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• 2022

The main idea of the framework is to seamlessly combine a reasonably accurate and fast surrogate model with the importance sampling strategy. Developing a surrogate model for predicting structures' dynamic responses is challenging because it involves high-dimensional inputs and outputs. For this purpose, a novel surrogate model based on cutting-edge deep learning architectures specialized for capturing temporal relationships within time-series data, namely Long-Short term memory layer and Transformer layer, is designed. After being properly trained, the surrogate model could be utilized in place of the finite element method to evaluate structures' responses without requiring any specialized software. On the other hand, the importance sampling is adopted to reduce the number of calculations required when computing the failure probability by drawing more relevant samples near critical areas. Thanks to the portability of the trained surrogate model, one can integrate the latter with the Importance sampling in a straightforward fashion, forming an efficient framework called TTIS, which represents double advantages: less number of calculations is needed, and the computational time of each calculation is significantly reduced. The proposed approach's applicability and efficiency are demonstrated through three examples with increasing complexity, involving a 1D beam, a 2D frame, and a 3D building structure. The results show that compared to the conventional Monte Carlo simulation, the proposed method can provide highly similar reliability results with a reduction of up to four orders of magnitudes in time complexity.

• 한국환경과학회지
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• 제33권2호
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• pp.113-119
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• 2024

In this study, the most suitable sampling methods for the bimodal mass distribution characteristics and individual particle analysis of atmospheric aerosols were investigated. Samples collected in Quartz, Teflon, and Nuclepore filters were analyzed for individual particles using scanning electron microscopy with an energy-dispersive X-ray spectrometer (SEM/EDS). Then, the pore diameter of the filter and the collection flow rate were determined using the theoretical collection efficiency calculation formula for two-stage separation sample collection of coarse and fine particles. The Nuclepore filter was found to be the most suitable filter for identifying the physical and chemical characteristics of atmospheric aerosols since it was able to separate the sample and count the different sized particles better than either Quartz or Teflon. Nuclepore filters with 8.0 ㎛ and 0.4 ㎛ pores were connected in series and exposed to a flow rate of 16.7 L/min for two-stage separation sampling. The results show that it is possible to separate and collect both coarse and fine particles. We expect that the proposed methodology will be used for future individual particle analysis of atmospheric aerosols and related research.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권10호
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• pp.3355-3372
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• 2022

Composing music is an inspired yet challenging task, in that the process involves many considerations such as assigning pitches, determining rhythm, and arranging accompaniment. Algorithmic composition aims to develop algorithms for music composition. Recently, algorithmic composition using artificial intelligence technologies received considerable attention. In particular, computational intelligence is widely used and achieves promising results in the creation of music. This paper attempts to provide a survey on the music generation based on the Monte Carlo (MC) algorithm. First, transform the MIDI music format files to digital data. Among these data, use the logistic fitting method to fit the time series, obtain the time distribution regular pattern. Except for time series, the converted data also includes duration, pitch, and velocity. Second, using MC simulation to deal with them summed up their distribution law respectively. The two main control parameters are the value of discrete sampling and standard deviation. Processing the above parameters and converting the data to MIDI file, then compared with the output generated by LSTM neural network, evaluate the music comprehensively.

• Journal of Mechanical Science and Technology
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• 제18권8호
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• pp.1297-1305
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• 2004

In this paper, we propose a new scheme for the discretization of nonlinear systems using Taylor series expansion and the zero-order hold assumption. This scheme is applied to the sampled-data representation of a non-affine nonlinear system with constant input time-delay. The mathematical expressions of the discretization scheme are presented and the ability of the algorithm is tested for some of the examples. The proposed scheme provides a finite-dimensional representation for nonlinear systems with time-delay enabling existing controller design techniques to be applied to them. For all the case studies, various sampling rates and time-delay values are considered.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 심포지엄 논문집 정보 및 제어부문
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• pp.125-127
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• 2005

In this paper, we propose a new scheme for the discretization of nonlinear systems using Taylor series expansion and the zero-order hold assumption. This scheme is applied to the sample-data representation of a nonlinear system with constant state tine-delay. The mathematical expressions of the discretization scheme are presented and the effect of the time-discretization method on key properties of nonlinear control system with state tine-delay, such as equilibrium properties and asymptotic ability, is examined. The proposed scheme provides a finite-dimensional representation for nonlinear systems with state time-delay enabling existing controller design techniques to be applied to then. The performance of the proposed discretization procedure is evaluated using a nonlinear system. For this nonlinear system, various sampling rates and time-delay values are considered.

• 한국시뮬레이션학회:학술대회논문집
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• 한국시뮬레이션학회 2001년도 The Seoul International Simulation Conference
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• pp.313-317
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• 2001

The approach to predict time series without neglecting the fluctuation in a short period is tried by using a digital FIR filter and a neural network. The differential waveform of the Nikkei average closing price is filtered by the FIR band-pass filter of 101 length. It is filtered into the five frequency bands of 0-1Hz, 1-2Hz, 2-3Hz, 3-4Hz and 4-5Hz by setting the sampling frequency 10Hz. The each filtered waveform is learned and forecasted by the neural network. The neural network of the back propagation method is adopted in the learning the waveform. By inputting the data of 20 days in the past, the prediction of 10 days ahead is carried out. After learning the time series of each frequency band by the neural network, the predicted data far each frequency band are obtained. The predicted waveforms of each frequency band are synthesized to obtain a final forecast. The waveform can be forecasted well as a whole.